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Poster
@ Poster Session 0 #32
Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings
Poster
@ Poster Session 0 #32
Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings
Poster
@ Poster Session 0 #32
Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings
Poster
@ Poster Session 0 #32
Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings
Spotlight
Curvature Regularization to Prevent Distortion in Graph Embedding
Expo Talk Panel
Sun Dec 06 05:00 AM -- 06:00 AM (PST)
The challenges and latest advances in the field of causal AI
[
Video 1]
Expo Talk Panel
Sun Dec 06 05:00 AM -- 06:00 AM (PST)
scikit-learn and fairness, tools and challenges
[
Video 1]
Expo Talk Panel
Sun Dec 06 06:00 AM -- 07:00 AM (PST)
How we leverage machine learning and AI to develop life-changing medicines - a case study with COVID-19.
[
Video 1]
Expo Talk Panel
Sun Dec 06 07:00 AM -- 08:00 AM (PST)
Accelerated Training with ML Compute on M1-Powered Macs
[
Video 1]
Expo Talk Panel
Sun Dec 06 07:00 AM -- 08:00 AM (PST)
Drifting Efficiently Through the Stratosphere Using Deep Reinforcement Learning
[
Video 1]
Expo Talk Panel
Sun Dec 06 08:00 AM -- 09:00 AM (PST)
Making boats fly by scaling Reinforcement Learning with Software 2.0
[
Video 1]
Expo Talk Panel
Sun Dec 06 09:00 AM -- 10:00 AM (PST)
Automating Wildlife Conservation for Cetaceans
[
Video 1]
Expo Talk Panel
Sun Dec 06 09:00 AM -- 10:00 AM (PST)
AI against COVID-19 at IBM Research
[
Video 1]
Expo Talk Panel
Sun Dec 06 10:00 AM -- 11:00 AM (PST)
Fairness, Explainability, and Privacy in AI/ML Systems
[
Video 1]
Expo Workshop
Sun Dec 06 10:00 AM -- 02:00 PM (PST)
Real World RL with Vowpal Wabbit: Beyond Contextual Bandits
[
Video 1]
Expo Workshop
Sun Dec 06 10:00 AM -- 02:05 PM (PST)
Mining and Learning with Graphs at Scale
[
Video 1]
Expo Talk Panel
Sun Dec 06 11:00 AM -- 12:00 PM (PST)
Challenges in the adoption of Machine Learning in Health Care
[
Video 1]
Expo Demonstration
Sun Dec 06 12:00 PM -- 01:00 PM (PST)
Using Sparse Quantization for Efficient Inference on Deep Neural Networks
[
Video 1]
Expo Talk Panel
Sun Dec 06 01:00 PM -- 02:00 PM (PST)
Human-Centered AI @ IBM Research –Automation versus Collaboration in the Age of AI
[
Video 1]
Expo Talk Panel
Sun Dec 06 01:00 PM -- 02:00 PM (PST)
Modern ML Meets Financial Markets: Insights and Challenges
[
Video 1]
Expo Talk Panel
Sun Dec 06 02:00 PM -- 03:00 PM (PST)
The Unpaved Path of Deploying Reliable and Human-Centered Machine Learning Systems
[
Video 1]
Expo Talk Panel
Sun Dec 06 02:00 PM -- 03:00 PM (PST)
Building Neural Interfaces: When Real and Artificial Neurons Meet
[
Video 1]
Expo Demonstration
Sun Dec 06 03:00 PM -- 04:00 PM (PST)
Beyond AutoML: AI Automation & Scaling
[
Video 1]
Expo Workshop
Sun Dec 06 03:00 PM -- 09:00 PM (PST)
DAQA – Domain Adaptation and Question Answering
[
Video 1]
Expo Talk Panel
Sun Dec 06 04:00 PM -- 05:00 PM (PST)
Scaling Data Labeling with Machine Learning
[
Video 1]
Expo Talk Panel
Sun Dec 06 05:00 PM -- 06:00 PM (PST)
Hypotheses Generation for Applications in Biomedicine and Gastronomy
[
Video 1]
Expo Demonstration
Sun Dec 06 06:00 PM -- 07:00 PM (PST)
Whale: Accelerate EasyTransfer training workloads within one unified distributed training framework
[
Video 1]
Expo Talk Panel
Sun Dec 06 06:00 PM -- 07:00 PM (PST)
Visually Debugging ML Models With Scale Nucleus
[
Video 1]
Expo Demonstration
Sun Dec 06 07:00 PM -- 08:00 PM (PST)
Accelerating Deep Learning for Entertainment with Sony's Neural Network Libraries and Console
[
Video 1]
Expo Talk Panel
Sun Dec 06 07:00 PM -- 08:00 PM (PST)
Driving New Frontiers of Machine Learning with Cruise
[
Video 1]
Expo Talk Panel
Sun Dec 06 08:00 PM -- 09:00 PM (PST)
Accelerating Eye Movement Research Via Smartphone Gaze
[
Video 1]
Expo Workshop
Sun Dec 06 08:00 PM -- 12:00 AM (PST)
MachineLearningforAll-InclusiveFinance
[
Video 1]
Expo Demonstration
Sun Dec 06 09:00 PM -- 10:00 PM (PST)
Discovering genetic medicines using the Deep Genomics AI Drug Discovery Platform
[
Video 1]
Expo Demonstration
Mon Dec 07 12:00 AM -- 01:00 AM (PST)
GAN Applications in Fashion Article Design and Outfit Rendering
[
Video 1]
Tutorial
Mon Dec 07 12:00 AM -- 02:30 AM (PST) @ Virtual
(Track2) Deeper Conversational AI
[
Slides]
[
Video Part 5]
Tutorial
Mon Dec 07 12:00 AM -- 02:30 AM (PST)
(Track1) Sketching and Streaming Algorithms
[
Video Part 1]
Tutorial
Mon Dec 07 02:30 AM -- 05:00 AM (PST)
(Track3) Designing Learning Dynamics
[
Video Part 4]
[
Video Part 6]
Tutorial
Mon Dec 07 02:30 AM -- 05:00 AM (PST)
(Track1) There and Back Again: A Tale of Slopes and Expectations
[
Video Part 1]
Affinity Workshop
Mon Dec 07 03:00 AM -- 01:15 PM (PST)
New In ML
Tutorial
Mon Dec 07 05:30 AM -- 08:00 AM (PST)
(Track2) Beyond Accuracy: Grounding Evaluation Metrics for Human-Machine Learning Systems
[
Video Part 1]
Tutorial
Mon Dec 07 05:30 AM -- 08:00 AM (PST)
(Track1) Where Neuroscience meets AI (And What’s in Store for the Future)
[
Video Part 1]
Affinity Workshop
Mon Dec 07 06:00 AM -- 12:30 PM (PST)
Black in AI
Affinity Workshop
Mon Dec 07 08:00 AM -- 07:00 PM (PST)
LXAI Research @ NeurIPS 2020
Tutorial
Mon Dec 07 08:00 AM -- 10:30 AM (PST) @ Virtual
(Track2) Practical Uncertainty Estimation and Out-of-Distribution Robustness in Deep Learning
[
Slides]
[
Video Part 1]
Tutorial
Mon Dec 07 08:00 AM -- 10:30 AM (PST)
(Track3) Offline Reinforcement Learning: From Algorithm Design to Practical Applications
[
Video Part 2]
Tutorial
Mon Dec 07 08:00 AM -- 10:30 AM (PST) @ Virtual
(Track1) Advances in Approximate Inference
[
Slides]
[
Video Part 4]
Tutorial
Mon Dec 07 11:00 AM -- 01:30 PM (PST)
(Track3) Policy Optimization in Reinforcement Learning
Tutorial
Mon Dec 07 11:00 AM -- 01:30 PM (PST)
(Track1) Abstraction & Reasoning in AI systems: Modern Perspectives
Tutorial
Mon Dec 07 11:00 AM -- 01:30 PM (PST)
(Track2) Machine Learning for Astrophysics and Astrophysics Problems for Machine Learning
Affinity Poster Session
Mon Dec 07 12:30 PM -- 02:30 PM (PST)
Joint Affinity Groups Poster Session
Tutorial
Mon Dec 07 01:30 PM -- 04:00 PM (PST)
(Track3) Deep Implicit Layers: Neural ODEs, Equilibrium Models, and Differentiable Optimization
[
Video Part 5]
Tutorial
Mon Dec 07 01:30 PM -- 04:00 PM (PST)
(Track1) Federated Learning and Analytics: Industry Meets Academia
[
Video Part 4]
Tutorial
Mon Dec 07 01:30 PM -- 04:00 PM (PST)
(Track2) Explaining Machine Learning Predictions: State-of-the-art, Challenges, and Opportunities
[
Video Part 1]
[
Video Part 3]
Invited Talk
Mon Dec 07 05:00 PM -- 07:00 PM (PST)
You Can’t Escape Hyperparameters and Latent Variables: Machine Learning as a Software Engineering Enterprise
Oral
Mon Dec 07 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Representation/Relational
Learning Physical Graph Representations from Visual Scenes
[ Paper ]
Oral
Mon Dec 07 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: COVID/Health/Bio Applications
When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes
[ Paper ]
Oral
Mon Dec 07 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Language/Audio Applications
Language Models are Few-Shot Learners
[ Paper ]
Oral
Mon Dec 07 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Reinforcement Learning
An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy Search
[ Paper ]
Oral
Mon Dec 07 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Representation/Relational
Multi-label Contrastive Predictive Coding
[ Paper ]
Oral
Mon Dec 07 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: COVID/Health/Bio Applications
Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement
[ Paper ]
Oral
Mon Dec 07 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Language/Audio Applications
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search
[ Paper ]
Oral
Mon Dec 07 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Novelty Search in Representational Space for Sample Efficient Exploration
[ Paper ]
Oral
Mon Dec 07 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Representation/Relational
Equivariant Networks for Hierarchical Structures
[ Paper ]
Oral
Mon Dec 07 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: COVID/Health/Bio Applications
Neural encoding with visual attention
[ Paper ]
Oral
Mon Dec 07 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Language/Audio Applications
The Cone of Silence: Speech Separation by Localization
[ Paper ]
Oral
Mon Dec 07 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design
[ Paper ]
Break
Mon Dec 07 06:45 PM -- 07:00 PM (PST)
Break
Break
Mon Dec 07 06:45 PM -- 07:00 PM (PST)
Break
Break
Mon Dec 07 06:45 PM -- 07:00 PM (PST)
Break
Break
Mon Dec 07 06:45 PM -- 07:00 PM (PST)
Break
Spotlight
Mon Dec 07 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Representation/Relational
On the Equivalence between Online and Private Learnability beyond Binary Classification
[ Paper ]
Spotlight
Mon Dec 07 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: COVID/Health/Bio Applications
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
[ Paper ]
Spotlight
Mon Dec 07 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Language/Audio Applications
Unsupervised Sound Separation Using Mixture Invariant Training
[ Paper ]
Spotlight
Mon Dec 07 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Reinforcement Learning
First Order Constrained Optimization in Policy Space
[ Paper ]
Spotlight
Mon Dec 07 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Representation/Relational
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
[ Paper ]
Spotlight
Mon Dec 07 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: COVID/Health/Bio Applications
Using noise to probe recurrent neural network structure and prune synapses
[ Paper ]
Spotlight
Mon Dec 07 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Language/Audio Applications
Investigating Gender Bias in Language Models Using Causal Mediation Analysis
[ Paper ]
Spotlight
Mon Dec 07 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Reinforcement Learning
CoinDICE: Off-Policy Confidence Interval Estimation
[ Paper ]
Spotlight
Mon Dec 07 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Representation/Relational
Joint Contrastive Learning with Infinite Possibilities
[ Paper ]
Spotlight
Mon Dec 07 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: COVID/Health/Bio Applications
Interpretable Sequence Learning for Covid-19 Forecasting
[ Paper ]
Spotlight
Mon Dec 07 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Language/Audio Applications
A Simple Language Model for Task-Oriented Dialogue
[ Paper ]
Spotlight
Mon Dec 07 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Reinforcement Learning
DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction
[ Paper ]
Spotlight
Mon Dec 07 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Representation/Relational
Neural Methods for Point-wise Dependency Estimation
[ Paper ]
Spotlight
Mon Dec 07 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: COVID/Health/Bio Applications
Kalman Filtering Attention for User Behavior Modeling in CTR Prediction
[ Paper ]
Spotlight
Mon Dec 07 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Language/Audio Applications
ConvBERT: Improving BERT with Span-based Dynamic Convolution
[ Paper ]
Spotlight
Mon Dec 07 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret
[ Paper ]
Q&A
Mon Dec 07 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Mon Dec 07 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Mon Dec 07 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Mon Dec 07 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Mon Dec 07 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Representation/Relational
Design Space for Graph Neural Networks
[ Paper ]
Spotlight
Mon Dec 07 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: COVID/Health/Bio Applications
Demixed shared component analysis of neural population data from multiple brain areas
[ Paper ]
Spotlight
Mon Dec 07 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Language/Audio Applications
Cross-lingual Retrieval for Iterative Self-Supervised Training
[ Paper ]
Spotlight
Mon Dec 07 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning
[ Paper ]
Spotlight
Mon Dec 07 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Representation/Relational
Debiased Contrastive Learning
[ Paper ]
Spotlight
Mon Dec 07 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: COVID/Health/Bio Applications
Minimax Optimal Nonparametric Estimation of Heterogeneous Treatment Effects
[ Paper ]
Spotlight
Mon Dec 07 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Language/Audio Applications
DynaBERT: Dynamic BERT with Adaptive Width and Depth
[ Paper ]
Spotlight
Mon Dec 07 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Bayesian Multi-type Mean Field Multi-agent Imitation Learning
[ Paper ]
Spotlight
Mon Dec 07 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Representation/Relational
The Autoencoding Variational Autoencoder
[ Paper ]
Spotlight
Mon Dec 07 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: COVID/Health/Bio Applications
The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models
[ Paper ]
Spotlight
Mon Dec 07 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Language/Audio Applications
Incorporating Pragmatic Reasoning Communication into Emergent Language
[ Paper ]
Spotlight
Mon Dec 07 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity
[ Paper ]
Q&A
Mon Dec 07 08:20 PM -- 08:30 PM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Mon Dec 07 08:20 PM -- 08:30 PM (PST) @ Orals & Spotlights: Representation/Relational
Unsupervised Representation Learning by Invariance Propagation
[ Paper ]
Spotlight
Mon Dec 07 08:20 PM -- 08:30 PM (PST) @ Orals & Spotlights: Language/Audio Applications
De-Anonymizing Text by Fingerprinting Language Generation
[ Paper ]
Spotlight
Mon Dec 07 08:20 PM -- 08:30 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Safe Reinforcement Learning via Curriculum Induction
[ Paper ]
Break
Mon Dec 07 08:30 PM -- 09:00 PM (PST)
Break
Q&A
Mon Dec 07 08:30 PM -- 08:40 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Mon Dec 07 08:30 PM -- 08:40 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Mon Dec 07 08:30 PM -- 08:40 PM (PST)
Joint Q&A for Preceeding Spotlights
Break
Mon Dec 07 08:40 PM -- 09:00 PM (PST)
Break
Break
Mon Dec 07 08:40 PM -- 09:00 PM (PST)
Break
Break
Mon Dec 07 08:40 PM -- 09:00 PM (PST)
Break
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #0
Rankmax: An Adaptive Projection Alternative to the Softmax Function
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #1
Field-wise Learning for Multi-field Categorical Data
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #2
Deep Diffusion-Invariant Wasserstein Distributional Classification
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #3
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #4
Efficient Clustering Based On A Unified View Of K-means And Ratio-cut
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #5
Probabilistic Fair Clustering
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #6
Sampling-Decomposable Generative Adversarial Recommender
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #7
Trading Personalization for Accuracy: Data Debugging in Collaborative Filtering
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #8
Ratio Trace Formulation of Wasserstein Discriminant Analysis
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #9
Coresets for Regressions with Panel Data
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #10
Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #11
Adversarial Learning for Robust Deep Clustering
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #12
Adversarial Counterfactual Learning and Evaluation for Recommender System
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #13
Adversarial Crowdsourcing Through Robust Rank-One Matrix Completion
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #14
Interventional Few-Shot Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #15
Neural Methods for Point-wise Dependency Estimation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #16
Multi-label Contrastive Predictive Coding
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #17
Self-Supervised Relationship Probing
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #18
Debiased Contrastive Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #19
The Autoencoding Variational Autoencoder
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #20
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #21
Unsupervised Data Augmentation for Consistency Training
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #22
Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #23
Hard Negative Mixing for Contrastive Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #24
Parametric Instance Classification for Unsupervised Visual Feature learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #25
VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #26
Unsupervised Representation Learning by Invariance Propagation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #27
Joint Contrastive Learning with Infinite Possibilities
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #28
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #29
Restoring Negative Information in Few-Shot Object Detection
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #30
One-sample Guided Object Representation Disassembling
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #31
Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #32
Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #33
Heavy-tailed Representations, Text Polarity Classification & Data Augmentation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #34
Hierarchical Poset Decoding for Compositional Generalization in Language
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #35
Strongly Incremental Constituency Parsing with Graph Neural Networks
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #36
A Simple Language Model for Task-Oriented Dialogue
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #37
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #38
Incorporating Pragmatic Reasoning Communication into Emergent Language
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #39
Learning Strategic Network Emergence Games
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #40
Fighting Copycat Agents in Behavioral Cloning from Observation Histories
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #41
Attention-Gated Brain Propagation: How the brain can implement reward-based error backpropagation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #42
Can the Brain Do Backpropagation? --- Exact Implementation of Backpropagation in Predictive Coding Networks
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #43
Demixed shared component analysis of neural population data from multiple brain areas
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #44
Neural encoding with visual attention
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #45
On Numerosity of Deep Neural Networks
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #46
Compact task representations as a normative model for higher-order brain activity
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #47
Using noise to probe recurrent neural network structure and prune synapses
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #48
An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #49
Language Models are Few-Shot Learners
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #50
Incorporating BERT into Parallel Sequence Decoding with Adapters
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #51
CogLTX: Applying BERT to Long Texts
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #52
MPNet: Masked and Permuted Pre-training for Language Understanding
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #53
MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #54
Towards Neural Programming Interfaces
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #55
Language Through a Prism: A Spectral Approach for Multiscale Language Representations
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #56
ColdGANs: Taming Language GANs with Cautious Sampling Strategies
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #57
ConvBERT: Improving BERT with Span-based Dynamic Convolution
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #58
Investigating Gender Bias in Language Models Using Causal Mediation Analysis
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #59
Cross-lingual Retrieval for Iterative Self-Supervised Training
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #60
DynaBERT: Dynamic BERT with Adaptive Width and Depth
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #62
Pre-training via Paraphrasing
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #63
Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #64
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #65
Big Bird: Transformers for Longer Sequences
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #66
Self-Supervised Generative Adversarial Compression
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #67
The Generalized Lasso with Nonlinear Observations and Generative Priors
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #68
Robust compressed sensing using generative models
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #69
Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #70
Fourier Spectrum Discrepancies in Deep Network Generated Images
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #71
Minimax Optimal Nonparametric Estimation of Heterogeneous Treatment Effects
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #72
Towards a Combinatorial Characterization of Bounded-Memory Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #73
The Power of Comparisons for Actively Learning Linear Classifiers
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #74
Estimating decision tree learnability with polylogarithmic sample complexity
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #75
Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #76
Matrix Inference and Estimation in Multi-Layer Models
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #77
Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #78
Limits on Testing Structural Changes in Ising Models
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #79
A Robust Functional EM Algorithm for Incomplete Panel Count Data
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #80
Weston-Watkins Hinge Loss and Ordered Partitions
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #81
On the Equivalence between Online and Private Learnability beyond Binary Classification
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #82
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #84
A Finite-Time Analysis of Two Time-Scale Actor-Critic Methods
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #85
Reinforcement Learning for Control with Multiple Frequencies
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #86
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #87
First Order Constrained Optimization in Policy Space
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #88
DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #89
Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #90
MOPO: Model-based Offline Policy Optimization
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #91
Trust the Model When It Is Confident: Masked Model-based Actor-Critic
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #92
Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large Games
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #93
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #94
MOReL: Model-Based Offline Reinforcement Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #95
Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #96
Independent Policy Gradient Methods for Competitive Reinforcement Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #97
Provably Good Batch Reinforcement Learning Without Great Exploration
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #98
(De)Randomized Smoothing for Certifiable Defense against Patch Attacks
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #99
Contrastive Learning with Adversarial Examples
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #100
CoADNet: Collaborative Aggregation-and-Distribution Networks for Co-Salient Object Detection
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #101
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #102
The Cone of Silence: Speech Separation by Localization
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #103
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #105
Swapping Autoencoder for Deep Image Manipulation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #106
LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-resolution and Beyond
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #107
Domain Generalization via Entropy Regularization
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #108
Self-Supervised Few-Shot Learning on Point Clouds
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #109
DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #110
CLEARER: Multi-Scale Neural Architecture Search for Image Restoration
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #111
Language and Visual Entity Relationship Graph for Agent Navigation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #112
Fast Fourier Convolution
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #113
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #114
The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #115
When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #116
Reinforced Molecular Optimization with Neighborhood-Controlled Grammars
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #117
Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #118
MRI Banding Removal via Adversarial Training
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #119
Learning to Select Best Forecast Tasks for Clinical Outcome Prediction
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #120
Interpretable Sequence Learning for Covid-19 Forecasting
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #121
Adversarial Attacks on Deep Graph Matching
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #122
Adversarial Sparse Transformer for Time Series Forecasting
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #123
Diversity can be Transferred: Output Diversification for White- and Black-box Attacks
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #124
Input-Aware Dynamic Backdoor Attack
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #125
Understanding Global Feature Contributions With Additive Importance Measures
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #126
Improving Policy-Constrained Kidney Exchange via Pre-Screening
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #127
Learning Black-Box Attackers with Transferable Priors and Query Feedback
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #128
De-Anonymizing Text by Fingerprinting Language Generation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #129
Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphs
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #130
Design Space for Graph Neural Networks
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #131
Learning Physical Graph Representations from Visual Scenes
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #132
Equivariant Networks for Hierarchical Structures
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #133
ARMA Nets: Expanding Receptive Field for Dense Prediction
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #134
Storage Efficient and Dynamic Flexible Runtime Channel Pruning via Deep Reinforcement Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #135
How to Characterize The Landscape of Overparameterized Convolutional Neural Networks
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #136
Towards Learning Convolutions from Scratch
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #137
Bayesian Attention Modules
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #138
Kalman Filtering Attention for User Behavior Modeling in CTR Prediction
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #139
Understanding and Exploring the Network with Stochastic Architectures
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #140
Neuron Merging: Compensating for Pruned Neurons
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #141
Position-based Scaled Gradient for Model Quantization and Pruning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #142
ShiftAddNet: A Hardware-Inspired Deep Network
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #143
Pruning neural networks without any data by iteratively conserving synaptic flow
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #144
Attribution Preservation in Network Compression for Reliable Network Interpretation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #145
Language as a Cognitive Tool to Imagine Goals in Curiosity Driven Exploration
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #146
An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy Search
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #147
Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #148
Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #149
Cooperative Heterogeneous Deep Reinforcement Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #150
The Mean-Squared Error of Double Q-Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #151
Novelty Search in Representational Space for Sample Efficient Exploration
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #152
Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #153
Decentralized TD Tracking with Linear Function Approximation and its Finite-Time Analysis
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #154
Robust Multi-Agent Reinforcement Learning with Model Uncertainty
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #155
Bayesian Multi-type Mean Field Multi-agent Imitation Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #156
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #157
Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #158
Safe Reinforcement Learning via Curriculum Induction
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #159
On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #160
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #161
Off-Policy Evaluation via the Regularized Lagrangian
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #162
Dynamic Regret of Policy Optimization in Non-Stationary Environments
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #163
Constrained episodic reinforcement learning in concave-convex and knapsack settings
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #164
Off-Policy Interval Estimation with Lipschitz Value Iteration
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #165
CoinDICE: Off-Policy Confidence Interval Estimation
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #166
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #167
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #168
Task-agnostic Exploration in Reinforcement Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #169
Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #170
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #171
Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #172
Minimax Value Interval for Off-Policy Evaluation and Policy Optimization
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #173
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #174
The Power of Predictions in Online Control
[ Paper ]
Poster
Mon Dec 07 09:00 PM -- 11:00 PM (PST) @ Poster Session 0 #570
Information Theoretic Regret Bounds for Online Nonlinear Control
[ Paper ]
Tutorial
Tue Dec 08 02:00 AM -- 02:50 AM (PST)
(Track2) Equivariant Networks Q&A
Tutorial
Tue Dec 08 03:00 AM -- 03:50 AM (PST)
(Track1) There and Back Again: A Tale of Slopes and Expectations Q&A
Invited Talk
Tue Dec 08 05:00 AM -- 07:00 AM (PST)
Feedback Control Perspectives on Learning
Demonstration
Tue Dec 08 06:00 AM -- 06:20 AM & Wed Dec 09 06:00 AM -- 06:20 AM (PST)
MONICA: MObile Neural voIce Command Assistant for mobile games
Oral
Tue Dec 08 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Clustering/Ranking
Exact Recovery of Mangled Clusters with Same-Cluster Queries
[ Paper ]
Oral
Tue Dec 08 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
Deep Energy-based Modeling of Discrete-Time Physics
[ Paper ]
Oral
Tue Dec 08 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Vision Applications
Deep Wiener Deconvolution: Wiener Meets Deep Learning for Image Deblurring
[ Paper ]
Oral
Tue Dec 08 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Deep Learning
Multiscale Deep Equilibrium Models
[ Paper ]
Oral
Tue Dec 08 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Improved Sample Complexity for Incremental Autonomous Exploration in MDPs
[ Paper ]
Oral
Tue Dec 08 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Social/Privacy
Adversarially Robust Streaming Algorithms via Differential Privacy
[ Paper ]
Oral
Tue Dec 08 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Learning Theory
No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium
[ Paper ]
Session
Tue Dec 08 06:00 AM -- 09:20 AM & Wed Dec 09 06:00 AM -- 09:20 AM (PST)
Demonstrations 1
Oral
Tue Dec 08 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Clustering/Ranking
Deep Transformation-Invariant Clustering
[ Paper ]
Oral
Tue Dec 08 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory
[ Paper ]
Oral
Tue Dec 08 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Vision Applications
Causal Intervention for Weakly-Supervised Semantic Segmentation
[ Paper ]
Oral
Tue Dec 08 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Deep Learning
On the Modularity of Hypernetworks
[ Paper ]
Oral
Tue Dec 08 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Escaping the Gravitational Pull of Softmax
[ Paper ]
Oral
Tue Dec 08 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Social/Privacy
Differentially Private Clustering: Tight Approximation Ratios
[ Paper ]
Oral
Tue Dec 08 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Learning Theory
Efficient active learning of sparse halfspaces with arbitrary bounded noise
[ Paper ]
Demonstration
Tue Dec 08 06:20 AM -- 06:40 AM & Wed Dec 09 06:20 AM -- 06:40 AM (PST)
tspDB: Time Series Predict DB
Oral
Tue Dec 08 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Clustering/Ranking
Partially View-aligned Clustering
[ Paper ]
Oral
Tue Dec 08 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
Dissecting Neural ODEs
[ Paper ]
Oral
Tue Dec 08 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Vision Applications
Convolutional Generation of Textured 3D Meshes
[ Paper ]
Oral
Tue Dec 08 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Deep Learning
Training Generative Adversarial Networks with Limited Data
[ Paper ]
Oral
Tue Dec 08 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Reinforcement Learning
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs
[ Paper ]
Oral
Tue Dec 08 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Social/Privacy
Locally private non-asymptotic testing of discrete distributions is faster using interactive mechanisms
[ Paper ]
Oral
Tue Dec 08 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Learning Theory
Learning Parities with Neural Networks
[ Paper ]
Demonstration
Tue Dec 08 06:40 AM -- 07:00 AM & Wed Dec 09 06:40 AM -- 07:00 AM (PST)
Probing Embedding Spaces in Deep Neural Networks
Break
Tue Dec 08 06:45 AM -- 07:00 AM (PST)
Break
Break
Tue Dec 08 06:45 AM -- 07:00 AM (PST)
Break
Break
Tue Dec 08 06:45 AM -- 07:00 AM (PST)
Break
Break
Tue Dec 08 06:45 AM -- 07:00 AM (PST)
Break
Affinity Workshop
Tue Dec 08 07:00 AM -- 12:30 PM (PST)
Queer in AI Workshop @ NeurIPS 2020
Demonstration
Tue Dec 08 07:00 AM -- 07:20 AM & Wed Dec 09 07:00 AM -- 07:20 AM (PST)
IBM Federated Learning Community Edition: An Interactive Demonstration
Spotlight
Tue Dec 08 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Clustering/Ranking
Simple and Scalable Sparse k-means Clustering via Feature Ranking
[ Paper ]
Spotlight
Tue Dec 08 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
Robust Density Estimation under Besov IPM Losses
[ Paper ]
Spotlight
Tue Dec 08 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Vision Applications
DISK: Learning local features with policy gradient
[ Paper ]
Spotlight
Tue Dec 08 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Deep Learning
MeshSDF: Differentiable Iso-Surface Extraction
[ Paper ]
Spotlight
Tue Dec 08 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Interferobot: aligning an optical interferometer by a reinforcement learning agent
[ Paper ]
Spotlight
Tue Dec 08 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Social/Privacy
Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates
[ Paper ]
Spotlight
Tue Dec 08 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Learning Theory
The Adaptive Complexity of Maximizing a Gross Substitutes Valuation
[ Paper ]
Spotlight
Tue Dec 08 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Clustering/Ranking
Simultaneous Preference and Metric Learning from Paired Comparisons
[ Paper ]
Spotlight
Tue Dec 08 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
Almost Surely Stable Deep Dynamics
[ Paper ]
Spotlight
Tue Dec 08 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Vision Applications
Wasserstein Distances for Stereo Disparity Estimation
[ Paper ]
Spotlight
Tue Dec 08 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Deep Learning
GAIT-prop: A biologically plausible learning rule derived from backpropagation of error
[ Paper ]
Spotlight
Tue Dec 08 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Reinforcement Learning
On Efficiency in Hierarchical Reinforcement Learning
[ Paper ]
Spotlight
Tue Dec 08 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Social/Privacy
Private Identity Testing for High-Dimensional Distributions
[ Paper ]
Spotlight
Tue Dec 08 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Learning Theory
Hitting the High Notes: Subset Selection for Maximizing Expected Order Statistics
[ Paper ]
Demonstration
Tue Dec 08 07:20 AM -- 07:40 AM & Wed Dec 09 07:20 AM -- 07:40 AM (PST)
MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning
Spotlight
Tue Dec 08 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Clustering/Ranking
Learning Optimal Representations with the Decodable Information Bottleneck
[ Paper ]
Spotlight
Tue Dec 08 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks
[ Paper ]
Spotlight
Tue Dec 08 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Vision Applications
Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance
[ Paper ]
Spotlight
Tue Dec 08 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Deep Learning
Monotone operator equilibrium networks
[ Paper ]
Spotlight
Tue Dec 08 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Finite-Time Analysis for Double Q-learning
[ Paper ]
Spotlight
Tue Dec 08 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Social/Privacy
Permute-and-Flip: A new mechanism for differentially private selection
[ Paper ]
Spotlight
Tue Dec 08 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Learning Theory
A Bandit Learning Algorithm and Applications to Auction Design
[ Paper ]
Affinity Workshop
Tue Dec 08 07:30 AM -- 11:00 AM (PST)
Muslims in ML
Spotlight
Tue Dec 08 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Clustering/Ranking
Manifold structure in graph embeddings
[ Paper ]
Spotlight
Tue Dec 08 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
A Theoretical Framework for Target Propagation
[ Paper ]
Spotlight
Tue Dec 08 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Vision Applications
Learning Semantic-aware Normalization for Generative Adversarial Networks
[ Paper ]
Spotlight
Tue Dec 08 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Deep Learning
What Do Neural Networks Learn When Trained With Random Labels?
[ Paper ]
Spotlight
Tue Dec 08 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes
[ Paper ]
Spotlight
Tue Dec 08 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Social/Privacy
Smoothed Analysis of Online and Differentially Private Learning
[ Paper ]
Spotlight
Tue Dec 08 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Learning Theory
An Optimal Elimination Algorithm for Learning a Best Arm
[ Paper ]
Demonstration
Tue Dec 08 07:40 AM -- 08:00 AM & Wed Dec 09 07:40 AM -- 08:00 AM (PST)
MosAIc: Finding Artistic Connections across Culture with Conditional Image Retrieval
Q&A
Tue Dec 08 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Tue Dec 08 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Clustering/Ranking
Self-Supervised Learning by Cross-Modal Audio-Video Clustering
[ Paper ]
Spotlight
Tue Dec 08 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
Training Generative Adversarial Networks by Solving Ordinary Differential Equations
[ Paper ]
Spotlight
Tue Dec 08 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Vision Applications
Neural Sparse Voxel Fields
[ Paper ]
Spotlight
Tue Dec 08 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Deep Learning
H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks
[ Paper ]
Spotlight
Tue Dec 08 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning
[ Paper ]
Spotlight
Tue Dec 08 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Social/Privacy
Optimal Private Median Estimation under Minimal Distributional Assumptions
[ Paper ]
Spotlight
Tue Dec 08 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Learning Theory
Second Order PAC-Bayesian Bounds for the Weighted Majority Vote
[ Paper ]
Demonstration
Tue Dec 08 08:00 AM -- 08:20 AM & Wed Dec 09 08:00 AM -- 08:20 AM (PST)
RetaiL: Open your own grocery store to reduce waste
Spotlight
Tue Dec 08 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Clustering/Ranking
Classification with Valid and Adaptive Coverage
[ Paper ]
Spotlight
Tue Dec 08 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
Information theoretic limits of learning a sparse rule
[ Paper ]
Spotlight
Tue Dec 08 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Vision Applications
3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data
[ Paper ]
Spotlight
Tue Dec 08 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Deep Learning
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks
[ Paper ]
Spotlight
Tue Dec 08 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Model-based Policy Optimization with Unsupervised Model Adaptation
[ Paper ]
Spotlight
Tue Dec 08 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Social/Privacy
Assisted Learning: A Framework for Multi-Organization Learning
[ Paper ]
Spotlight
Tue Dec 08 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Learning Theory
PAC-Bayesian Bound for the Conditional Value at Risk
[ Paper ]
Spotlight
Tue Dec 08 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Clustering/Ranking
On ranking via sorting by estimated expected utility
[ Paper ]
Spotlight
Tue Dec 08 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
Constant-Expansion Suffices for Compressed Sensing with Generative Priors
[ Paper ]
Spotlight
Tue Dec 08 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Vision Applications
Learning to Detect Objects with a 1 Megapixel Event Camera
[ Paper ]
Spotlight
Tue Dec 08 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Deep Learning
The phase diagram of approximation rates for deep neural networks
[ Paper ]
Spotlight
Tue Dec 08 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
[ Paper ]
Spotlight
Tue Dec 08 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Social/Privacy
Higher-Order Certification For Randomized Smoothing
[ Paper ]
Spotlight
Tue Dec 08 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Learning Theory
Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Evolvability
[ Paper ]
Demonstration
Tue Dec 08 08:20 AM -- 08:40 AM & Wed Dec 09 08:20 AM -- 08:40 AM (PST)
PrototypeML: Visual Design of Arbitrarily Complex Neural Networks
Q&A
Tue Dec 08 08:20 AM -- 08:30 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 08:20 AM -- 08:30 AM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Tue Dec 08 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Dynamical Sys/Density/Sparsity
Logarithmic Pruning is All You Need
[ Paper ]
Spotlight
Tue Dec 08 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Vision Applications
A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection
[ Paper ]
Spotlight
Tue Dec 08 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Deep Learning
Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient
[ Paper ]
Spotlight
Tue Dec 08 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Sample-Efficient Reinforcement Learning of Undercomplete POMDPs
[ Paper ]
Spotlight
Tue Dec 08 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Learning Theory
Hedging in games: Faster convergence of external and swap regrets
[ Paper ]
Break
Tue Dec 08 08:30 AM -- 09:00 AM (PST)
Break
Q&A
Tue Dec 08 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Tue Dec 08 08:30 AM -- 08:40 AM (PST) @ Orals & Spotlights: Learning Theory
Online Bayesian Persuasion
[ Paper ]
Break
Tue Dec 08 08:40 AM -- 09:00 AM (PST)
Break
Break
Tue Dec 08 08:40 AM -- 09:00 AM (PST)
Break
Break
Tue Dec 08 08:40 AM -- 09:00 AM (PST)
Break
Demonstration
Tue Dec 08 08:40 AM -- 09:00 AM & Wed Dec 09 08:40 AM -- 09:00 AM (PST)
A Knowledge Graph Reasoning Prototype
Q&A
Tue Dec 08 08:40 AM -- 08:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Demonstration
Tue Dec 08 09:00 AM -- 09:20 AM & Wed Dec 09 09:00 AM -- 09:20 AM (PST)
Shared Interest: Human Annotations vs. AI Saliency
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #61
Latent Template Induction with Gumbel-CRFs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #175
Federated Principal Component Analysis
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #176
Learning Differential Equations that are Easy to Solve
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #177
Learning Rich Rankings
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #178
Self-supervised Co-Training for Video Representation Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #179
Prophet Attention: Predicting Attention with Future Attention
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #180
Audeo: Audio Generation for a Silent Performance Video
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #181
Cascaded Text Generation with Markov Transformers
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #182
All Word Embeddings from One Embedding
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #183
Data Diversification: A Simple Strategy For Neural Machine Translation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #184
Learning Sparse Prototypes for Text Generation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #185
A Discrete Variational Recurrent Topic Model without the Reparametrization Trick
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #186
AViD Dataset: Anonymized Videos from Diverse Countries
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #187
Convolutional Tensor-Train LSTM for Spatio-Temporal Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #189
End-to-End Learning and Intervention in Games
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #190
Cross-validation Confidence Intervals for Test Error
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #191
Learning Robust Decision Policies from Observational Data
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #192
Improved Sample Complexity for Incremental Autonomous Exploration in MDPs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #193
Self-Imitation Learning via Generalized Lower Bound Q-learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #194
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #195
One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #196
An operator view of policy gradient methods
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #197
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #198
Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #199
How to Learn a Useful Critic? Model-based Action-Gradient-Estimator Policy Optimization
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #200
The Value Equivalence Principle for Model-Based Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #201
Doubly Robust Off-Policy Value and Gradient Estimation for Deterministic Policies
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #202
Neurosymbolic Reinforcement Learning with Formally Verified Exploration
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #203
Near-Optimal Reinforcement Learning with Self-Play
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #204
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #205
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #206
Deep Multimodal Fusion by Channel Exchanging
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #207
Learning Representations from Audio-Visual Spatial Alignment
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #208
Knowledge Augmented Deep Neural Networks for Joint Facial Expression and Action Unit Recognition
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #209
Causal Intervention for Weakly-Supervised Semantic Segmentation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #210
Generative View Synthesis: From Single-view Semantics to Novel-view Images
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #211
Labelling unlabelled videos from scratch with multi-modal self-supervision
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #212
Unfolding the Alternating Optimization for Blind Super Resolution
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #213
Video Frame Interpolation without Temporal Priors
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #214
Delving into the Cyclic Mechanism in Semi-supervised Video Object Segmentation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #215
Color Visual Illusions: A Statistics-based Computational Model
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #216
A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #217
Make One-Shot Video Object Segmentation Efficient Again
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #218
SIRI: Spatial Relation Induced Network For Spatial Description Resolution
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #219
Multi-Plane Program Induction with 3D Box Priors
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #220
RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #221
Unsupervised object-centric video generation and decomposition in 3D
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #222
Dissecting Neural ODEs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #223
On ranking via sorting by estimated expected utility
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #224
Constant-Expansion Suffices for Compressed Sensing with Generative Priors
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #225
Model Interpretability through the Lens of Computational Complexity
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #226
Agnostic $Q$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #227
Smoothed Analysis of Online and Differentially Private Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #228
Non-Convex SGD Learns Halfspaces with Adversarial Label Noise
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #229
Hardness of Learning Neural Networks with Natural Weights
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #230
Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Evolvability
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #231
The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #232
The phase diagram of approximation rates for deep neural networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #233
A Dynamical Central Limit Theorem for Shallow Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #234
Learning Bounds for Risk-sensitive Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #235
Agnostic Learning of a Single Neuron with Gradient Descent
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #236
Information theoretic limits of learning a sparse rule
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #237
From Finite to Countable-Armed Bandits
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #238
Optimal Best-arm Identification in Linear Bandits
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #239
Restless-UCB, an Efficient and Low-complexity Algorithm for Online Restless Bandits
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #240
Finite Continuum-Armed Bandits
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #241
Adversarial Blocking Bandits
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #242
Inference for Batched Bandits
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #243
Online Algorithm for Unsupervised Sequential Selection with Contextual Information
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #244
Adversarial Attacks on Linear Contextual Bandits
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #245
Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #246
Finding All $\epsilon$-Good Arms in Stochastic Bandits
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #247
An Optimal Elimination Algorithm for Learning a Best Arm
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #248
Instance-wise Feature Grouping
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #249
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #250
Online Planning with Lookahead Policies
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #251
Escaping the Gravitational Pull of Softmax
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #252
Online Bayesian Persuasion
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #253
KFC: A Scalable Approximation Algorithm for $k$−center Fair Clustering
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #254
CoinPress: Practical Private Mean and Covariance Estimation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #255
Auditing Differentially Private Machine Learning: How Private is Private SGD?
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #256
Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #257
Smoothly Bounding User Contributions in Differential Privacy
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #258
Learning from Mixtures of Private and Public Populations
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #259
A Computational Separation between Private Learning and Online Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #260
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #261
Improving Sparse Vector Technique with Renyi Differential Privacy
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #262
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #263
Private Identity Testing for High-Dimensional Distributions
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #264
Optimal Private Median Estimation under Minimal Distributional Assumptions
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #265
Learning discrete distributions: user vs item-level privacy
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #266
Locally private non-asymptotic testing of discrete distributions is faster using interactive mechanisms
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #267
Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #268
Phase retrieval in high dimensions: Statistical and computational phase transitions
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #269
Higher-Order Spectral Clustering of Directed Graphs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #270
Deep Transformation-Invariant Clustering
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #271
Faster DBSCAN via subsampled similarity queries
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #272
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #273
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #274
Exact Recovery of Mangled Clusters with Same-Cluster Queries
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #275
Simple and Scalable Sparse k-means Clustering via Feature Ranking
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #276
Efficient Clustering for Stretched Mixtures: Landscape and Optimality
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #277
Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #278
Classification with Valid and Adaptive Coverage
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #279
Self-Supervised Learning by Cross-Modal Audio-Video Clustering
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #280
HyNet: Learning Local Descriptor with Hybrid Similarity Measure and Triplet Loss
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #281
Distributionally Robust Local Non-parametric Conditional Estimation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #282
Differentially Private Clustering: Tight Approximation Ratios
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #283
Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #284
Learning to Decode: Reinforcement Learning for Decoding of Sparse Graph-Based Channel Codes
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #285
Non-Euclidean Universal Approximation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #286
WoodFisher: Efficient Second-Order Approximation for Neural Network Compression
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #287
Deep Transformers with Latent Depth
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #288
Movement Pruning: Adaptive Sparsity by Fine-Tuning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #289
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #290
Pruning Filter in Filter
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #292
The Lottery Ticket Hypothesis for Pre-trained BERT Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #293
The Generalization-Stability Tradeoff In Neural Network Pruning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #294
Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #295
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #296
HYDRA: Pruning Adversarially Robust Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #297
Logarithmic Pruning is All You Need
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #299
Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #300
Higher-Order Certification For Randomized Smoothing
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #301
Adversarial robustness via robust low rank representations
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #302
Denoised Smoothing: A Provable Defense for Pretrained Classifiers
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #303
Margins are Insufficient for Explaining Gradient Boosting
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #304
On the Power of Louvain in the Stochastic Block Model
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #305
Robust large-margin learning in hyperbolic space
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #306
Self-Learning Transformations for Improving Gaze and Head Redirection
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #307
Exactly Computing the Local Lipschitz Constant of ReLU Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #308
Optimizing Mode Connectivity via Neuron Alignment
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #309
An Efficient Framework for Clustered Federated Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #310
On the distance between two neural networks and the stability of learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #311
One Ring to Rule Them All: Certifiably Robust Geometric Perception with Outliers
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #312
Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #313
Consequences of Misaligned AI
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #314
Certified Defense to Image Transformations via Randomized Smoothing
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #315
Certifying Strategyproof Auction Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #316
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #317
Improving robustness against common corruptions by covariate shift adaptation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #318
Deeply Learned Spectral Total Variation Decomposition
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #319
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #320
Multiscale Deep Equilibrium Models
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #321
Faithful Embeddings for Knowledge Base Queries
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #322
GradAug: A New Regularization Method for Deep Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #323
Monotone operator equilibrium networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #324
Hierarchical nucleation in deep neural networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #325
What Do Neural Networks Learn When Trained With Random Labels?
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #326
H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #327
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #328
Throughput-Optimal Topology Design for Cross-Silo Federated Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #329
Wavelet Flow: Fast Training of High Resolution Normalizing Flows
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #330
Woodbury Transformations for Deep Generative Flows
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #331
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #332
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #333
Regret in Online Recommendation Systems
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #334
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #335
Myersonian Regression
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #336
On Convergence of Nearest Neighbor Classifiers over Feature Transformations
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #337
Learning Utilities and Equilibria in Non-Truthful Auctions
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #338
Contextual Reserve Price Optimization in Auctions via Mixed Integer Programming
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #339
Secretary and Online Matching Problems with Machine Learned Advice
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #340
On the Error Resistance of Hinge-Loss Minimization
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #341
Polynomial-Time Computation of Optimal Correlated Equilibria in Two-Player Extensive-Form Games with Public Chance Moves and Beyond
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #342
Chaos, Extremism and Optimism: Volume Analysis of Learning in Games
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #343
A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #344
A Bandit Learning Algorithm and Applications to Auction Design
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #345
No-regret Learning in Price Competitions under Consumer Reference Effects
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #346
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #347
Partially View-aligned Clustering
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #348
MeshSDF: Differentiable Iso-Surface Extraction
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #349
Joint Policy Search for Multi-agent Collaboration with Imperfect Information
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #350
On Infinite-Width Hypernetworks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #351
Training Generative Adversarial Networks with Limited Data
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #352
Reinforcement Learning with Combinatorial Actions: An Application to Vehicle Routing
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #353
A Self-Tuning Actor-Critic Algorithm
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #354
Residual Force Control for Agile Human Behavior Imitation and Extended Motion Synthesis
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #355
See, Hear, Explore: Curiosity via Audio-Visual Association
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #356
Finite-Time Analysis for Double Q-learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #357
Adaptive Discretization for Model-Based Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #358
Object Goal Navigation using Goal-Oriented Semantic Exploration
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #359
Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #360
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #361
A new convergent variant of Q-learning with linear function approximation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #362
A Unified Switching System Perspective and Convergence Analysis of Q-Learning Algorithms
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #363
Adversarially Robust Streaming Algorithms via Differential Privacy
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #365
A Topological Filter for Learning with Label Noise
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #366
Learning by Minimizing the Sum of Ranked Range
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #367
Partial Optimal Transport with applications on Positive-Unlabeled Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #368
Assisted Learning: A Framework for Multi-Organization Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #369
Learning Disentangled Representations and Group Structure of Dynamical Environments
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #370
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #371
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #372
Improving Natural Language Processing Tasks with Human Gaze-Guided Neural Attention
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #373
COBE: Contextualized Object Embeddings from Narrated Instructional Video
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #374
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #375
Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #376
Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #377
Probably Approximately Correct Constrained Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #378
Sharp uniform convergence bounds through empirical centralization
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #379
Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #380
Gaussian Gated Linear Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #381
BayReL: Bayesian Relational Learning for Multi-omics Data Integration
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #382
Manifold structure in graph embeddings
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #383
GAIT-prop: A biologically plausible learning rule derived from backpropagation of error
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #384
Learning to Learn with Feedback and Local Plasticity
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #385
A Theoretical Framework for Target Propagation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #386
Inductive Quantum Embedding
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #387
Optimizing Neural Networks via Koopman Operator Theory
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #388
Biological credit assignment through dynamic inversion of feedforward networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #389
On 1/n neural representation and robustness
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #390
Real World Games Look Like Spinning Tops
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #391
Quantitative Propagation of Chaos for SGD in Wide Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #392
Network size and size of the weights in memorization with two-layers neural networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #393
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #394
All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #395
Soft Contrastive Learning for Visual Localization
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #396
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #397
Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View Consistency
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #398
Cross-Scale Internal Graph Neural Network for Image Super-Resolution
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #399
GPS-Net: Graph-based Photometric Stereo Network
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #400
Convolutional Generation of Textured 3D Meshes
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #401
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #402
Neural Sparse Representation for Image Restoration
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #403
GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #404
Watch out! Motion is Blurring the Vision of Your Deep Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #405
Continuous Object Representation Networks: Novel View Synthesis without Target View Supervision
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #406
Learning Semantic-aware Normalization for Generative Adversarial Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #407
3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #408
Learning to Detect Objects with a 1 Megapixel Event Camera
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #409
A Loss Function for Generative Neural Networks Based on Watson’s Perceptual Model
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #410
GANSpace: Discovering Interpretable GAN Controls
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #411
Deep Energy-based Modeling of Discrete-Time Physics
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #412
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #413
Weak Form Generalized Hamiltonian Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #414
Disentangling by Subspace Diffusion
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #415
Simultaneous Preference and Metric Learning from Paired Comparisons
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #416
Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #417
Hold me tight! Influence of discriminative features on deep network boundaries
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #418
Training Generative Adversarial Networks by Solving Ordinary Differential Equations
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #419
Sparse Graphical Memory for Robust Planning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #420
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #421
Bayesian Robust Optimization for Imitation Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #422
Learning Parities with Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #423
Learning the Linear Quadratic Regulator from Nonlinear Observations
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #424
Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #425
Stateful Posted Pricing with Vanishing Regret via Dynamic Deterministic Markov Decision Processes
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #426
On the Theory of Transfer Learning: The Importance of Task Diversity
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #427
Online Agnostic Boosting via Regret Minimization
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #428
Minimax Classification with 0-1 Loss and Performance Guarantees
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #429
Robust Density Estimation under Besov IPM Losses
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #430
Online Multitask Learning with Long-Term Memory
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #431
Improving Local Identifiability in Probabilistic Box Embeddings
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #432
Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #433
Synthetic Data Generators -- Sequential and Private
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #434
Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #435
Statistical-Query Lower Bounds via Functional Gradients
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #436
PAC-Bayes Learning Bounds for Sample-Dependent Priors
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #437
Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #438
Decision trees as partitioning machines to characterize their generalization properties
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #439
A Limitation of the PAC-Bayes Framework
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #440
Conditioning and Processing: Techniques to Improve Information-Theoretic Generalization Bounds
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #441
Second Order PAC-Bayesian Bounds for the Weighted Majority Vote
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #442
PAC-Bayes Analysis Beyond the Usual Bounds
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #443
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #444
Probabilistic Orientation Estimation with Matrix Fisher Distributions
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #445
Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #446
Inference Stage Optimization for Cross-scenario 3D Human Pose Estimation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #447
Deep Wiener Deconvolution: Wiener Meets Deep Learning for Image Deblurring
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #448
Calibrating CNNs for Lifelong Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #449
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #450
Diverse Image Captioning with Context-Object Split Latent Spaces
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #451
An Analysis of SVD for Deep Rotation Estimation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #452
DISK: Learning local features with policy gradient
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #453
Wasserstein Distances for Stereo Disparity Estimation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #454
GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #455
On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #456
A Dictionary Approach to Domain-Invariant Learning in Deep Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #457
Balanced Meta-Softmax for Long-Tailed Visual Recognition
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #458
Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #459
Sparse Symplectically Integrated Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #460
Node Embeddings and Exact Low-Rank Representations of Complex Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #461
Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #462
Towards Understanding Hierarchical Learning: Benefits of Neural Representations
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #463
Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #464
Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #465
Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #466
Universal guarantees for decision tree induction via a higher-order splitting criterion
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #467
Learning Restricted Boltzmann Machines with Sparse Latent Variables
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #468
The Adaptive Complexity of Maximizing a Gross Substitutes Valuation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #469
Hedging in games: Faster convergence of external and swap regrets
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #470
Nonasymptotic Guarantees for Spiked Matrix Recovery with Generative Priors
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #471
In search of robust measures of generalization
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #472
On Convergence and Generalization of Dropout Training
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #473
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #474
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #475
Correspondence learning via linearly-invariant embedding
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #476
PIE-NET: Parametric Inference of Point Cloud Edges
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #477
Neural Non-Rigid Tracking
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #478
Continuous Surface Embeddings
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #479
Learning to Orient Surfaces by Self-supervised Spherical CNNs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #480
SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Images
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #481
Neural Unsigned Distance Fields for Implicit Function Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #482
Skeleton-bridged Point Completion: From Global Inference to Local Adjustment
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #483
Rotation-Invariant Local-to-Global Representation Learning for 3D Point Cloud
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #484
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #485
Dense Correspondences between Human Bodies via Learning Transformation Synchronization on Graphs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #486
3D Shape Reconstruction from Vision and Touch
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #487
Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #488
Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #489
Neural Sparse Voxel Fields
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #490
RepPoints v2: Verification Meets Regression for Object Detection
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #491
Efficient Contextual Bandits with Continuous Actions
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #492
Collapsing Bandits and Their Application to Public Health Intervention
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #493
Learning to Play Sequential Games versus Unknown Opponents
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #494
Interferobot: aligning an optical interferometer by a reinforcement learning agent
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #495
Reinforcement Learning in Factored MDPs: Oracle-Efficient Algorithms and Tighter Regret Bounds for the Non-Episodic Setting
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #496
Reinforcement Learning with Feedback Graphs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #497
A Unifying View of Optimism in Episodic Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #498
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #499
On Reward-Free Reinforcement Learning with Linear Function Approximation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #500
On Efficiency in Hierarchical Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #501
Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #502
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #503
Belief-Dependent Macro-Action Discovery in POMDPs using the Value of Information
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #504
High-Throughput Synchronous Deep RL
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #505
AttendLight: Universal Attention-Based Reinforcement Learning Model for Traffic Signal Control
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #507
Dynamic Submodular Maximization
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #508
Adaptive Shrinkage Estimation for Streaming Graphs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #509
Near-Optimal Comparison Based Clustering
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #510
Impossibility Results for Grammar-Compressed Linear Algebra
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #511
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #512
Submodular Meta-Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #513
Fairness in Streaming Submodular Maximization: Algorithms and Hardness
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #514
Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack Constraint
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #515
Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #516
Efficient active learning of sparse halfspaces with arbitrary bounded noise
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #517
Learning Structured Distributions From Untrusted Batches: Faster and Simpler
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #519
Outlier Robust Mean Estimation with Subgaussian Rates via Stability
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #520
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #521
Hitting the High Notes: Subset Selection for Maximizing Expected Order Statistics
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #522
PAC-Bayesian Bound for the Conditional Value at Risk
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #523
Universal Function Approximation on Graphs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #524
Model Class Reliance for Random Forests
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #525
Hypersolvers: Toward Fast Continuous-Depth Models
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #526
Almost Surely Stable Deep Dynamics
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #527
Learning Optimal Representations with the Decodable Information Bottleneck
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #528
Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #529
Measuring Systematic Generalization in Neural Proof Generation with Transformers
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #530
Online Decision Based Visual Tracking via Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #531
On the Modularity of Hypernetworks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #532
Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating Point
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #533
Counterexample-Guided Learning of Monotonic Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #534
Permute-and-Flip: A new mechanism for differentially private selection
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #535
No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #536
Spike and slab variational Bayes for high dimensional logistic regression
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #537
How does Weight Correlation Affect Generalisation Ability of Deep Neural Networks?
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #538
Learning discrete distributions with infinite support
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #539
Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #540
A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #541
Instance-based Generalization in Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #542
Efficient Planning in Large MDPs with Weak Linear Function Approximation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #543
Multi-agent active perception with prediction rewards
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #544
Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #545
The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #546
Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #547
Model-based Policy Optimization with Unsupervised Model Adaptation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #548
Deep Reinforcement and InfoMax Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #549
Zap Q-Learning With Nonlinear Function Approximation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #550
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #551
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #552
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #553
Sample-Efficient Reinforcement Learning of Undercomplete POMDPs
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #554
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #555
Self-Supervised MultiModal Versatile Networks
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #556
Deep Subspace Clustering with Data Augmentation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #557
Learning Retrospective Knowledge with Reverse Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #558
The MAGICAL Benchmark for Robust Imitation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #559
Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #560
Counterfactual Data Augmentation using Locally Factored Dynamics
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #561
POMDPs in Continuous Time and Discrete Spaces
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #562
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #563
Forethought and Hindsight in Credit Assignment
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #564
Learning Multi-Agent Communication through Structured Attentive Reasoning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #565
MultiON: Benchmarking Semantic Map Memory using Multi-Object Navigation
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #566
Influence-Augmented Online Planning for Complex Environments
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #567
Security Analysis of Safe and Seldonian Reinforcement Learning Algorithms
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #568
Provably Efficient Neural GTD for Off-Policy Learning
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #569
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay
[ Paper ]
Poster
Tue Dec 08 09:00 AM -- 11:00 AM (PST) @ Poster Session 1 #1020
Comparator-Adaptive Convex Bandits
[ Paper ]
Symposium
Tue Dec 08 12:00 PM -- 04:00 PM (PST)
COVID-19 Symposium Day 1
Tutorial
Tue Dec 08 12:00 PM -- 12:50 PM (PST)
(Track3) Offline Reinforcement Learning: From Algorithm Design to Practical Applications Q&A
Tutorial
Tue Dec 08 01:00 PM -- 01:50 PM (PST)
(Track1) Sketching and Streaming Algorithms Q&A
Tutorial
Tue Dec 08 02:00 PM -- 02:50 PM (PST)
(Track2) Beyond Accuracy: Grounding Evaluation Metrics for Human-Machine Learning Systems Q&A
Invited Talk
Tue Dec 08 05:00 PM -- 07:00 PM (PST)
Robustness, Verification, Privacy: Addressing Machine Learning Adversaries
[
Video 1]
Demonstration
Tue Dec 08 06:00 PM -- 06:20 PM & Wed Dec 09 06:00 PM -- 06:20 PM (PST)
LMdiff: A Visual Diff Tool to Compare LanguageModels
Oral
Tue Dec 08 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Vision Applications
Space-Time Correspondence as a Contrastive Random Walk
[ Paper ]
Oral
Tue Dec 08 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
Implicit Neural Representations with Periodic Activation Functions
[ Paper ]
Oral
Tue Dec 08 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement
[ Paper ]
Session
Tue Dec 08 06:00 PM -- 09:20 PM & Wed Dec 09 06:00 PM -- 09:20 PM (PST)
Demonstrations 2
Oral
Tue Dec 08 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Vision Applications
Rethinking Pre-training and Self-training
[ Paper ]
Oral
Tue Dec 08 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation
[ Paper ]
Oral
Tue Dec 08 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Learning Individually Inferred Communication for Multi-Agent Cooperation
[ Paper ]
Demonstration
Tue Dec 08 06:20 PM -- 06:40 PM & Wed Dec 09 06:20 PM -- 06:40 PM (PST)
AI Assisted Data Labeling
Oral
Tue Dec 08 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Vision Applications
Do Adversarially Robust ImageNet Models Transfer Better?
[ Paper ]
Oral
Tue Dec 08 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators
[ Paper ]
Oral
Tue Dec 08 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory
[ Paper ]
Demonstration
Tue Dec 08 06:40 PM -- 07:00 PM & Wed Dec 09 06:40 PM -- 07:00 PM (PST)
Automated dataset extraction from SEC filings
Break
Tue Dec 08 06:45 PM -- 07:00 PM (PST)
Break
Break
Tue Dec 08 06:45 PM -- 07:00 PM (PST)
Break
Break
Tue Dec 08 06:45 PM -- 07:00 PM (PST)
Break
Demonstration
Tue Dec 08 07:00 PM -- 07:20 PM & Wed Dec 09 07:00 PM -- 07:20 PM (PST)
Generating Novelty in Open-World Multi-Agent Strategic Board Games
Spotlight
Tue Dec 08 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Vision Applications
Self-Supervised Visual Representation Learning from Hierarchical Grouping
[ Paper ]
Spotlight
Tue Dec 08 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures
[ Paper ]
Spotlight
Tue Dec 08 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Reinforcement Learning with Augmented Data
[ Paper ]
Spotlight
Tue Dec 08 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Vision Applications
Learning Affordance Landscapes for Interaction Exploration in 3D Environments
[ Paper ]
Spotlight
Tue Dec 08 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization
[ Paper ]
Spotlight
Tue Dec 08 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Sub-sampling for Efficient Non-Parametric Bandit Exploration
[ Paper ]
Demonstration
Tue Dec 08 07:20 PM -- 07:40 PM & Wed Dec 09 07:20 PM -- 07:40 PM (PST)
Fast and Automatic Visual Label Conflict Resolution
Spotlight
Tue Dec 08 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Vision Applications
Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D
[ Paper ]
Spotlight
Tue Dec 08 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
Compositional Visual Generation with Energy Based Models
[ Paper ]
Spotlight
Tue Dec 08 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Language-Conditioned Imitation Learning for Robot Manipulation Tasks
[ Paper ]
Spotlight
Tue Dec 08 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Vision Applications
Large-Scale Adversarial Training for Vision-and-Language Representation Learning
[ Paper ]
Spotlight
Tue Dec 08 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
Certified Monotonic Neural Networks
[ Paper ]
Spotlight
Tue Dec 08 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Reinforcement Learning
High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization
[ Paper ]
Demonstration
Tue Dec 08 07:40 PM -- 08:00 PM & Wed Dec 09 07:40 PM -- 08:00 PM (PST)
DeepRacing AI - Autonomous Motorsport Racing
Q&A
Tue Dec 08 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Tue Dec 08 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Vision Applications
Measuring Robustness to Natural Distribution Shifts in Image Classification
[ Paper ]
Spotlight
Tue Dec 08 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing
[ Paper ]
Spotlight
Tue Dec 08 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Policy Improvement via Imitation of Multiple Oracles
[ Paper ]
Demonstration
Tue Dec 08 08:00 PM -- 08:20 PM & Wed Dec 09 08:00 PM -- 08:20 PM (PST)
ColliFlow: A Library for Executing Collaborative Intelligence Graphs
Spotlight
Tue Dec 08 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Vision Applications
Curriculum By Smoothing
[ Paper ]
Spotlight
Tue Dec 08 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
On Correctness of Automatic Differentiation for Non-Differentiable Functions
[ Paper ]
Spotlight
Tue Dec 08 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning
[ Paper ]
Spotlight
Tue Dec 08 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Vision Applications
Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies
[ Paper ]
Spotlight
Tue Dec 08 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
The Complete Lasso Tradeoff Diagram
[ Paper ]
Spotlight
Tue Dec 08 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Avoiding Side Effects in Complex Environments
[ Paper ]
Demonstration
Tue Dec 08 08:20 PM -- 08:40 PM & Wed Dec 09 08:20 PM -- 08:40 PM (PST)
Musical Speech: A Transformer-based Composition Tool
Q&A
Tue Dec 08 08:20 PM -- 08:30 PM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Tue Dec 08 08:20 PM -- 08:30 PM (PST) @ Orals & Spotlights: Deep Learning/Theory
Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality
[ Paper ]
Spotlight
Tue Dec 08 08:20 PM -- 08:30 PM (PST) @ Orals & Spotlights: Reinforcement Learning
Preference-based Reinforcement Learning with Finite-Time Guarantees
[ Paper ]
Break
Tue Dec 08 08:30 PM -- 09:00 PM (PST)
Break
Q&A
Tue Dec 08 08:30 PM -- 08:40 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Tue Dec 08 08:30 PM -- 08:40 PM (PST)
Joint Q&A for Preceeding Spotlights
Break
Tue Dec 08 08:40 PM -- 09:00 PM (PST)
Break
Break
Tue Dec 08 08:40 PM -- 09:00 PM (PST)
Break
Demonstration
Tue Dec 08 08:40 PM -- 09:00 PM & Wed Dec 09 08:40 PM -- 09:00 PM (PST)
xLP: Explainable Link Prediction Demo
Demonstration
Tue Dec 08 09:00 PM -- 09:20 PM & Wed Dec 09 09:00 PM -- 09:20 PM (PST)
Coreference Resolution for Neutralizing Gendered Pronouns
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #83
Conservative Q-Learning for Offline Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #571
Towards Playing Full MOBA Games with Deep Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #572
Federated Bayesian Optimization via Thompson Sampling
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #573
Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #574
Reinforcement Learning with Augmented Data
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #575
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #576
Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #577
Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #578
Succinct and Robust Multi-Agent Communication With Temporal Message Control
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #579
Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #580
Learning Individually Inferred Communication for Multi-Agent Cooperation
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #581
Emergent Reciprocity and Team Formation from Randomized Uncertain Social Preferences
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #582
Marginal Utility for Planning in Continuous or Large Discrete Action Spaces
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #583
A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning Instances
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #584
Softmax Deep Double Deterministic Policy Gradients
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #585
Non-Crossing Quantile Regression for Distributional Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #586
Improving Generalization in Reinforcement Learning with Mixture Regularization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #588
Differentiable Meta-Learning of Bandit Policies
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #589
Latent Bandits Revisited
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #590
Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #591
Sub-sampling for Efficient Non-Parametric Bandit Exploration
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #592
Online Learning in Contextual Bandits using Gated Linear Networks
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #593
High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #594
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #595
RD$^2$: Reward Decomposition with Representation Decomposition
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #596
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #597
Learning Guidance Rewards with Trajectory-space Smoothing
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #598
Avoiding Side Effects in Complex Environments
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #599
Reward-rational (implicit) choice: A unifying formalism for reward learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #600
Planning with General Objective Functions: Going Beyond Total Rewards
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #601
Preference-based Reinforcement Learning with Finite-Time Guarantees
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #602
Is Long Horizon RL More Difficult Than Short Horizon RL?
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #603
Online Meta-Critic Learning for Off-Policy Actor-Critic Methods
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #604
POMO: Policy Optimization with Multiple Optima for Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #605
Error Bounds of Imitating Policies and Environments
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #606
Model-based Adversarial Meta-Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #608
Offline Imitation Learning with a Misspecified Simulator
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #609
Policy Improvement via Imitation of Multiple Oracles
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #610
Toward the Fundamental Limits of Imitation Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #611
Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #612
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #613
Multi-task Batch Reinforcement Learning with Metric Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #614
Multi-Task Reinforcement Learning with Soft Modularization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #615
Generalized Hindsight for Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #616
Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #617
BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #618
Steady State Analysis of Episodic Reinforcement Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #619
The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #620
Learning Disentangled Representations of Videos with Missing Data
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #621
Cycle-Contrast for Self-Supervised Video Representation Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #622
Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #623
Blind Video Temporal Consistency via Deep Video Prior
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #624
Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #625
Space-Time Correspondence as a Contrastive Random Walk
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #626
Do Adversarially Robust ImageNet Models Transfer Better?
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #627
Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region Refinement
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #628
Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #629
Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability Volumes
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #630
COOT: Cooperative Hierarchical Transformer for Video-Text Representation Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #631
Stochastic Normalization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #632
Curriculum By Smoothing
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #633
Focus of Attention Improves Information Transfer in Visual Features
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #634
Semantic Visual Navigation by Watching YouTube Videos
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #635
Lipschitz-Certifiable Training with a Tight Outer Bound
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #636
Efficient Exact Verification of Binarized Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #637
Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #638
CASTLE: Regularization via Auxiliary Causal Graph Discovery
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #639
Multi-Stage Influence Function
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #640
On Completeness-aware Concept-Based Explanations in Deep Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #641
Adaptive Online Estimation of Piecewise Polynomial Trends
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #642
Robust Optimization for Fairness with Noisy Protected Groups
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #643
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #644
The Discrete Gaussian for Differential Privacy
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #645
Locally Differentially Private (Contextual) Bandits Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #646
A Scalable Approach for Privacy-Preserving Collaborative Machine Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #647
Privacy Amplification via Random Check-Ins
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #648
The Flajolet-Martin Sketch Itself Preserves Differential Privacy: Private Counting with Minimal Space
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #649
Breaking the Communication-Privacy-Accuracy Trilemma
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #650
Towards practical differentially private causal graph discovery
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #651
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #652
Relative gradient optimization of the Jacobian term in unsupervised deep learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #653
Multipole Graph Neural Operator for Parametric Partial Differential Equations
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #654
Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #655
Proximity Operator of the Matrix Perspective Function and its Applications
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #656
Improved Algorithms for Convex-Concave Minimax Optimization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #657
Decentralized Accelerated Proximal Gradient Descent
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #658
Optimal Epoch Stochastic Gradient Descent Ascent Methods for Min-Max Optimization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #659
Lower Bounds and Optimal Algorithms for Personalized Federated Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #660
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #661
A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #662
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #663
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #664
Optimal Query Complexity of Secure Stochastic Convex Optimization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #665
Approximate Cross-Validation with Low-Rank Data in High Dimensions
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #666
Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #667
A Closer Look at Accuracy vs. Robustness
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #668
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #669
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #670
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #671
Adversarial Distributional Training for Robust Deep Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #672
On the Trade-off between Adversarial and Backdoor Robustness
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #673
An Efficient Adversarial Attack for Tree Ensembles
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #674
Adversarial Self-Supervised Contrastive Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #675
Adversarial Weight Perturbation Helps Robust Generalization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #676
Large-Scale Adversarial Training for Vision-and-Language Representation Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #677
GreedyFool: Distortion-Aware Sparse Adversarial Attack
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #678
Consistency Regularization for Certified Robustness of Smoothed Classifiers
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #679
Measuring Robustness to Natural Distribution Shifts in Image Classification
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #680
Certified Monotonic Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #681
Backpropagating Linearly Improves Transferability of Adversarial Examples
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #682
Practical No-box Adversarial Attacks against DNNs
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #683
Learning to Adapt to Evolving Domains
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #684
MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #685
Heuristic Domain Adaptation
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #686
Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #687
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #688
Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #689
Implicit Neural Representations with Periodic Activation Functions
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #690
Rethinking Pre-training and Self-training
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #691
MetaSDF: Meta-Learning Signed Distance Functions
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #692
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #693
Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #695
Autoregressive Score Matching
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #696
Compositional Visual Generation with Energy Based Models
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #697
How does This Interaction Affect Me? Interpretable Attribution for Feature Interactions
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #698
Domain Adaptation as a Problem of Inference on Graphical Models
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #699
Fast Unbalanced Optimal Transport on a Tree
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #700
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #701
O(n) Connections are Expressive Enough: Universal Approximability of Sparse Transformers
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #702
A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #703
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #704
Is Plug-in Solver Sample-Efficient for Feature-based Reinforcement Learning?
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #705
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #706
Preference learning along multiple criteria: A game-theoretic perspective
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #707
On Correctness of Automatic Differentiation for Non-Differentiable Functions
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #708
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #709
Cooperative Multi-player Bandit Optimization
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #710
Neutralizing Self-Selection Bias in Sampling for Sortition
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #711
The Complete Lasso Tradeoff Diagram
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #712
Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #713
Distributional Robustness with IPMs and links to Regularization and GANs
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #714
Towards Convergence Rate Analysis of Random Forests for Classification
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #715
Learning to Mutate with Hypergradient Guided Population
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #716
Robust Disentanglement of a Few Factors at a Time using rPU-VAE
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #717
Self-Supervised Graph Transformer on Large-Scale Molecular Data
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #718
TorsionNet: A Reinforcement Learning Approach to Sequential Conformer Search
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #719
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #720
TaylorGAN: Neighbor-Augmented Policy Update Towards Sample-Efficient Natural Language Generation
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #721
Towards Interpretable Natural Language Understanding with Explanations as Latent Variables
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #722
Learning to summarize with human feedback
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #723
Language-Conditioned Imitation Learning for Robot Manipulation Tasks
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #724
Guiding Deep Molecular Optimization with Genetic Exploration
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #725
What is being transferred in transfer learning?
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #726
What shapes feature representations? Exploring datasets, architectures, and training
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #727
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #728
Benchmarking Deep Learning Interpretability in Time Series Predictions
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #729
Stochastic Deep Gaussian Processes over Graphs
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #730
Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #731
Rethinking Learnable Tree Filter for Generic Feature Transform
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #732
SOLOv2: Dynamic and Fast Instance Segmentation
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #733
HOI Analysis: Integrating and Decomposing Human-Object Interaction
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #734
RANet: Region Attention Network for Semantic Segmentation
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #735
ICNet: Intra-saliency Correlation Network for Co-Saliency Detection
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #736
Few-Cost Salient Object Detection with Adversarial-Paced Learning
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #737
Detecting Hands and Recognizing Physical Contact in the Wild
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #738
Targeted Adversarial Perturbations for Monocular Depth Prediction
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #739
Self-Supervised Visual Representation Learning from Hierarchical Grouping
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #740
Learning Affordance Landscapes for Interaction Exploration in 3D Environments
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #741
Deep Variational Instance Segmentation
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #742
Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic Segmentation
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #743
Fine-Grained Dynamic Head for Object Detection
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #744
Learning About Objects by Learning to Interact with Them
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #745
Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #1146
Optimal visual search based on a model of target detectability in natural images
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #1163
Online Influence Maximization under Linear Threshold Model
[ Paper ]
Poster
Tue Dec 08 09:00 PM -- 11:00 PM (PST) @ Poster Session 2 #1190
Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of Distributions
[ Paper ]
Tutorial
Wed Dec 09 01:00 AM -- 01:50 AM (PST)
(Track1) Advances in Approximate Inference Q&A
Affinity Workshop
Wed Dec 09 01:40 AM -- 06:00 PM (PST)
Women in Machine Learning
Tutorial
Wed Dec 09 03:00 AM -- 03:50 AM (PST)
(Track2) Explaining Machine Learning Predictions: State-of-the-art, Challenges, and Opportunities Q&A
Invited Talk (Posner Lecture)
Wed Dec 09 05:00 AM -- 07:00 AM (PST)
The Real AI Revolution
Oral
Wed Dec 09 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
High-Fidelity Generative Image Compression
[ Paper ]
Oral
Wed Dec 09 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
Continual Deep Learning by Functional Regularisation of Memorable Past
[ Paper ]
Oral
Wed Dec 09 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
Learning with Operator-valued Kernels in Reproducing Kernel Krein Spaces
[ Paper ]
Oral
Wed Dec 09 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Deep Learning
Ultra-Low Precision 4-bit Training of Deep Neural Networks
[ Paper ]
Oral
Wed Dec 09 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
Network-to-Network Translation with Conditional Invertible Neural Networks
[ Paper ]
Oral
Wed Dec 09 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles
[ Paper ]
Oral
Wed Dec 09 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Optimization
Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
Oral
Wed Dec 09 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
Learning Composable Energy Surrogates for PDE Order Reduction
[ Paper ]
Oral
Wed Dec 09 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
Look-ahead Meta Learning for Continual Learning
[ Paper ]
Oral
Wed Dec 09 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
Kernel Methods Through the Roof: Handling Billions of Points Efficiently
[ Paper ]
Oral
Wed Dec 09 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Deep Learning
Reservoir Computing meets Recurrent Kernels and Structured Transforms
[ Paper ]
Oral
Wed Dec 09 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
Causal Imitation Learning With Unobserved Confounders
[ Paper ]
Oral
Wed Dec 09 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Metric-Free Individual Fairness in Online Learning
[ Paper ]
Oral
Wed Dec 09 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Optimization
Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form
[ Paper ]
Oral
Wed Dec 09 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems
[ Paper ]
Oral
Wed Dec 09 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
NeuMiss networks: differentiable programming for supervised learning with missing values.
[ Paper ]
Oral
Wed Dec 09 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
A Group-Theoretic Framework for Data Augmentation
[ Paper ]
Oral
Wed Dec 09 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Deep Learning
The interplay between randomness and structure during learning in RNNs
[ Paper ]
Oral
Wed Dec 09 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
Gradient Estimation with Stochastic Softmax Tricks
[ Paper ]
Oral
Wed Dec 09 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Fair regression via plug-in estimator and recalibration with statistical guarantees
[ Paper ]
Oral
Wed Dec 09 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Optimization
Acceleration with a Ball Optimization Oracle
[ Paper ]
Break
Wed Dec 09 06:45 AM -- 07:00 AM (PST)
Break
Break
Wed Dec 09 06:45 AM -- 07:00 AM (PST)
Break
Break
Wed Dec 09 06:45 AM -- 07:00 AM (PST)
Break
Break
Wed Dec 09 06:45 AM -- 07:00 AM (PST)
Break
Break
Wed Dec 09 06:45 AM -- 07:00 AM (PST)
Break
Oral
Wed Dec 09 06:45 AM -- 07:00 AM (PST) @ Orals & Spotlights: Optimization
Convex optimization based on global lower second-order models
[ Paper ]
Spotlight
Wed Dec 09 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
Compositional Generalization by Learning Analytical Expressions
[ Paper ]
Spotlight
Wed Dec 09 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
Meta-trained agents implement Bayes-optimal agents
[ Paper ]
Spotlight
Wed Dec 09 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
A mathematical model for automatic differentiation in machine learning
[ Paper ]
Spotlight
Wed Dec 09 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Deep Learning
What if Neural Networks had SVDs?
[ Paper ]
Spotlight
Wed Dec 09 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs
[ Paper ]
Spotlight
Wed Dec 09 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay
[ Paper ]
Spotlight
Wed Dec 09 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Optimization
Adam with Bandit Sampling for Deep Learning
[ Paper ]
Spotlight
Wed Dec 09 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
Modern Hopfield Networks and Attention for Immune Repertoire Classification
[ Paper ]
Spotlight
Wed Dec 09 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
Linear Dynamical Systems as a Core Computational Primitive
[ Paper ]
Spotlight
Wed Dec 09 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
A kernel test for quasi-independence
[ Paper ]
Spotlight
Wed Dec 09 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Deep Learning
Practical Quasi-Newton Methods for Training Deep Neural Networks
[ Paper ]
Spotlight
Wed Dec 09 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
A Randomized Algorithm to Reduce the Support of Discrete Measures
[ Paper ]
Spotlight
Wed Dec 09 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Differentially-Private Federated Linear Bandits
[ Paper ]
Spotlight
Wed Dec 09 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Optimization
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling
[ Paper ]
Spotlight
Wed Dec 09 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA
[ Paper ]
Spotlight
Wed Dec 09 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels
[ Paper ]
Spotlight
Wed Dec 09 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
Fourier Sparse Leverage Scores and Approximate Kernel Learning
[ Paper ]
Spotlight
Wed Dec 09 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Deep Learning
Triple descent and the two kinds of overfitting: where & why do they appear?
[ Paper ]
Spotlight
Wed Dec 09 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
A/B Testing in Dense Large-Scale Networks: Design and Inference
[ Paper ]
Spotlight
Wed Dec 09 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Adversarial Training is a Form of Data-dependent Operator Norm Regularization
[ Paper ]
Spotlight
Wed Dec 09 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Optimization
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method
[ Paper ]
Spotlight
Wed Dec 09 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
A causal view of compositional zero-shot recognition
[ Paper ]
Spotlight
Wed Dec 09 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
Uncertainty-aware Self-training for Few-shot Text Classification
[ Paper ]
Spotlight
Wed Dec 09 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
BOSS: Bayesian Optimization over String Spaces
[ Paper ]
Spotlight
Wed Dec 09 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Deep Learning
On the linearity of large non-linear models: when and why the tangent kernel is constant
[ Paper ]
Spotlight
Wed Dec 09 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
DisARM: An Antithetic Gradient Estimator for Binary Latent Variables
[ Paper ]
Spotlight
Wed Dec 09 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Prediction with Corrupted Expert Advice
[ Paper ]
Spotlight
Wed Dec 09 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Optimization
Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity
[ Paper ]
Q&A
Wed Dec 09 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Wed Dec 09 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist
[ Paper ]
Spotlight
Wed Dec 09 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
HiPPO: Recurrent Memory with Optimal Polynomial Projections
[ Paper ]
Spotlight
Wed Dec 09 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
Fast geometric learning with symbolic matrices
[ Paper ]
Spotlight
Wed Dec 09 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Deep Learning
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy
[ Paper ]
Spotlight
Wed Dec 09 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
Off-Policy Evaluation and Learning for External Validity under a Covariate Shift
[ Paper ]
Spotlight
Wed Dec 09 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses
[ Paper ]
Spotlight
Wed Dec 09 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Optimization
Minibatch Stochastic Approximate Proximal Point Methods
[ Paper ]
Spotlight
Wed Dec 09 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
Barking up the right tree: an approach to search over molecule synthesis DAGs
[ Paper ]
Spotlight
Wed Dec 09 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity
[ Paper ]
Spotlight
Wed Dec 09 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
Training Stronger Baselines for Learning to Optimize
[ Paper ]
Spotlight
Wed Dec 09 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Deep Learning
Proximal Mapping for Deep Regularization
[ Paper ]
Spotlight
Wed Dec 09 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding
[ Paper ]
Spotlight
Wed Dec 09 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Towards Safe Policy Improvement for Non-Stationary MDPs
[ Paper ]
Spotlight
Wed Dec 09 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Optimization
Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems
[ Paper ]
Spotlight
Wed Dec 09 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
Learning Object-Centric Representations of Multi-Object Scenes from Multiple Views
[ Paper ]
Spotlight
Wed Dec 09 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
Leap-Of-Thought: Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge
[ Paper ]
Spotlight
Wed Dec 09 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
Learning Linear Programs from Optimal Decisions
[ Paper ]
Spotlight
Wed Dec 09 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Deep Learning
BoxE: A Box Embedding Model for Knowledge Base Completion
[ Paper ]
Spotlight
Wed Dec 09 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
Differentiable Causal Discovery from Interventional Data
[ Paper ]
Spotlight
Wed Dec 09 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations
[ Paper ]
Spotlight
Wed Dec 09 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Optimization
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms
[ Paper ]
Q&A
Wed Dec 09 08:20 AM -- 08:30 AM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Wed Dec 09 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
Experimental design for MRI by greedy policy search
[ Paper ]
Spotlight
Wed Dec 09 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning
[ Paper ]
Spotlight
Wed Dec 09 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Kernel Methods/Optimization
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems
[ Paper ]
Spotlight
Wed Dec 09 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks
[ Paper ]
Spotlight
Wed Dec 09 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
[ Paper ]
Spotlight
Wed Dec 09 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Optimization
Linearly Converging Error Compensated SGD
[ Paper ]
Q&A
Wed Dec 09 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Wed Dec 09 08:30 AM -- 08:40 AM (PST) @ Orals & Spotlights: COVID/Applications/Composition
How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?
[ Paper ]
Spotlight
Wed Dec 09 08:30 AM -- 08:40 AM (PST) @ Orals & Spotlights: Optimization
Learning Augmented Energy Minimization via Speed Scaling
[ Paper ]
Spotlight
Wed Dec 09 08:30 AM -- 08:40 AM (PST) @ Orals & Spotlights: Continual/Meta/Misc Learning
Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients
[ Paper ]
Spotlight
Wed Dec 09 08:30 AM -- 08:40 AM (PST) @ Orals & Spotlights: Probabilistic/Causality
Efficient semidefinite-programming-based inference for binary and multi-class MRFs
[ Paper ]
Spotlight
Wed Dec 09 08:30 AM -- 08:40 AM (PST) @ Orals & Spotlights: Social/Adversarial Learning
Understanding Gradient Clipping in Private SGD: A Geometric Perspective
[ Paper ]
Break
Wed Dec 09 08:40 AM -- 09:00 AM (PST)
Break
Q&A
Wed Dec 09 08:40 AM -- 08:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 08:40 AM -- 08:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 08:40 AM -- 08:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 08:40 AM -- 08:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 08:40 AM -- 08:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Break
Wed Dec 09 08:50 AM -- 09:00 AM (PST)
Break
Break
Wed Dec 09 08:50 AM -- 09:00 AM (PST)
Break
Break
Wed Dec 09 08:50 AM -- 09:00 AM (PST)
Break
Break
Wed Dec 09 08:50 AM -- 09:00 AM (PST)
Break
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #291
Model Fusion via Optimal Transport
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #746
What if Neural Networks had SVDs?
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #747
Understanding and Improving Fast Adversarial Training
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #748
Posterior Re-calibration for Imbalanced Datasets
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #749
Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #750
GCN meets GPU: Decoupling “When to Sample” from “How to Sample”
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #751
Improving model calibration with accuracy versus uncertainty optimization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #752
Deep Evidential Regression
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #753
Practical Quasi-Newton Methods for Training Deep Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #754
Ultra-Low Precision 4-bit Training of Deep Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #755
Improving Neural Network Training in Low Dimensional Random Bases
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #756
Bandit Samplers for Training Graph Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #757
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #758
Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #759
Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #760
MomentumRNN: Integrating Momentum into Recurrent Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #761
Why are Adaptive Methods Good for Attention Models?
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #762
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #763
Dark Experience for General Continual Learning: a Strong, Simple Baseline
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #764
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #765
Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #766
Continual Deep Learning by Functional Regularisation of Memorable Past
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #767
Look-ahead Meta Learning for Continual Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #768
A Combinatorial Perspective on Transfer Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #769
Continual Learning in Low-rank Orthogonal Subspaces
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #770
Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #771
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #772
Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #773
Task-Robust Model-Agnostic Meta-Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #774
Learning to Learn Variational Semantic Memory
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #775
Continuous Meta-Learning without Tasks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #776
Auxiliary Task Reweighting for Minimum-data Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #777
Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #778
Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #779
PLANS: Neuro-Symbolic Program Learning from Videos
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #780
Probabilistic Linear Solvers for Machine Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #781
A/B Testing in Dense Large-Scale Networks: Design and Inference
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #782
Dual Instrumental Variable Regression
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #783
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #784
Gradient Regularized V-Learning for Dynamic Treatment Regimes
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #785
Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #786
Causal Estimation with Functional Confounders
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #787
Counterfactual Prediction for Bundle Treatment
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #788
Minimax Estimation of Conditional Moment Models
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #789
Off-Policy Evaluation and Learning for External Validity under a Covariate Shift
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #790
Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #791
Multi-task Causal Learning with Gaussian Processes
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #792
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #793
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #794
Compositional Generalization via Neural-Symbolic Stack Machines
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #795
Learning Invariants through Soft Unification
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #796
Linear Disentangled Representations and Unsupervised Action Estimation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #797
Identifying Mislabeled Data using the Area Under the Margin Ranking
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #798
A Bayesian Nonparametrics View into Deep Representations
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #799
Learning Invariances in Neural Networks from Training Data
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #800
Inverse Learning of Symmetries
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #801
Post-training Iterative Hierarchical Data Augmentation for Deep Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #802
Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #803
Goal-directed Generation of Discrete Structures with Conditional Generative Models
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #804
CoSE: Compositional Stroke Embeddings
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #805
A Causal View on Robustness of Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #806
Regularizing Towards Permutation Invariance In Recurrent Models
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #807
STLnet: Signal Temporal Logic Enforced Multivariate Recurrent Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #808
Generative causal explanations of black-box classifiers
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #809
Assessing SATNet's Ability to Solve the Symbol Grounding Problem
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #810
Towards Better Generalization of Adaptive Gradient Methods
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #811
Adam with Bandit Sampling for Deep Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #812
Random Reshuffling: Simple Analysis with Vast Improvements
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #813
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #814
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #815
A Catalyst Framework for Minimax Optimization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #816
Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax Problems
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #817
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #818
Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #819
An Improved Analysis of Stochastic Gradient Descent with Momentum
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #820
Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #821
Online Robust Regression via SGD on the l1 loss
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #822
Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #823
Large-Scale Methods for Distributionally Robust Optimization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #824
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #825
Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #826
Provable Overlapping Community Detection in Weighted Graphs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #827
Improving Inference for Neural Image Compression
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #828
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #829
Kernel Methods Through the Roof: Handling Billions of Points Efficiently
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #830
Discovering conflicting groups in signed networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #831
StratLearner: Learning a Strategy for Misinformation Prevention in Social Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #832
Learning Differentiable Programs with Admissible Neural Heuristics
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #833
Neural Execution Engines: Learning to Execute Subroutines
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #834
Multimodal Graph Networks for Compositional Generalization in Visual Question Answering
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #835
RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #836
SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #837
Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #838
Fast geometric learning with symbolic matrices
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #839
Synbols: Probing Learning Algorithms with Synthetic Datasets
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #840
Evaluating Attribution for Graph Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #841
Accelerating Reinforcement Learning through GPU Atari Emulation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #842
Adaptive Gradient Quantization for Data-Parallel SGD
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #843
Universally Quantized Neural Compression
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #844
Searching for Low-Bit Weights in Quantized Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #845
Bayesian Bits: Unifying Quantization and Pruning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #846
FleXOR: Trainable Fractional Quantization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #847
Robust Quantization: One Model to Rule Them All
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #848
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #849
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #850
DisARM: An Antithetic Gradient Estimator for Binary Latent Variables
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #851
Efficient semidefinite-programming-based inference for binary and multi-class MRFs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #852
Gradient Estimation with Stochastic Softmax Tricks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #853
Quantized Variational Inference
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #854
Approximation Based Variance Reduction for Reparameterization Gradients
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #855
VarGrad: A Low-Variance Gradient Estimator for Variational Inference
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #856
Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #857
AutoPrivacy: Automated Layer-wise Parameter Selection for Secure Neural Network Inference
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #858
Group-Fair Online Allocation in Continuous Time
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #859
Fair Hierarchical Clustering
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #860
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #861
Metric-Free Individual Fairness in Online Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #862
Fair regression via plug-in estimator and recalibration with statistical guarantees
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #863
Fair Multiple Decision Making Through Soft Interventions
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #864
Intra-Processing Methods for Debiasing Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #865
Ensuring Fairness Beyond the Training Data
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #866
Fair Performance Metric Elicitation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #867
Fairness without Demographics through Adversarially Reweighted Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #868
Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #869
How do fair decisions fare in long-term qualification?
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #870
Fair regression with Wasserstein barycenters
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #871
Learning Certified Individually Fair Representations
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #872
Fairness with Overlapping Groups; a Probabilistic Perspective
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #873
Consistent Plug-in Classifiers for Complex Objectives and Constraints
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #874
Causal Discovery in Physical Systems from Videos
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #875
Causal Imitation Learning With Unobserved Confounders
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #876
A Class of Algorithms for General Instrumental Variable Models
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #877
Active Invariant Causal Prediction: Experiment Selection through Stability
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #878
Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #879
Deep Structural Causal Models for Tractable Counterfactual Inference
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #880
Reconsidering Generative Objectives For Counterfactual Reasoning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #881
High-recall causal discovery for autocorrelated time series with latent confounders
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #882
Applications of Common Entropy for Causal Inference
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #883
Entropic Causal Inference: Identifiability and Finite Sample Results
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #884
General Transportability of Soft Interventions: Completeness Results
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #885
Learning Causal Effects via Weighted Empirical Risk Minimization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #886
Differentiable Causal Discovery from Interventional Data
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #887
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #888
Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #889
A polynomial-time algorithm for learning nonparametric causal graphs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #890
Linear Time Sinkhorn Divergences using Positive Features
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #891
Learning Kernel Tests Without Data Splitting
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #892
Learning with Operator-valued Kernels in Reproducing Kernel Krein Spaces
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #893
A kernel test for quasi-independence
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #894
Hard Shape-Constrained Kernel Machines
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #895
Statistical Optimal Transport posed as Learning Kernel Embedding
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #896
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #897
Continuous Regularized Wasserstein Barycenters
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #898
Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #899
Multi-Fidelity Bayesian Optimization via Deep Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #900
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #901
Hybrid Models for Learning to Branch
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #902
Interior Point Solving for LP-based prediction+optimisation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #903
Curriculum learning for multilevel budgeted combinatorial problems
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #904
BOSS: Bayesian Optimization over String Spaces
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #905
An implicit function learning approach for parametric modal regression
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #906
Adversarial Example Games
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #907
Robust Pre-Training by Adversarial Contrastive Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #908
Provably Robust Metric Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #909
A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #910
Adversarial Training is a Form of Data-dependent Operator Norm Regularization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #911
Adversarial Robustness of Supervised Sparse Coding
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #912
Boosting Adversarial Training with Hypersphere Embedding
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #913
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #914
DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #915
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #916
Adversarially Robust Few-Shot Learning: A Meta-Learning Approach
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #917
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #918
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #919
Robustness of Bayesian Neural Networks to Gradient-Based Attacks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #920
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #921
On Adaptive Attacks to Adversarial Example Defenses
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #922
High-Fidelity Generative Image Compression
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #923
Attribute Prototype Network for Zero-Shot Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #924
Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #925
Variational Interaction Information Maximization for Cross-domain Disentanglement
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #926
Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #927
Few-shot Image Generation with Elastic Weight Consolidation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #928
DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #929
Generating Correct Answers for Progressive Matrices Intelligence Tests
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #930
GramGAN: Deep 3D Texture Synthesis From 2D Exemplars
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #931
Network-to-Network Translation with Conditional Invertible Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #932
Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #933
Instance Selection for GANs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #934
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #935
ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #936
Smoothed Geometry for Robust Attribution
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #937
Neural Networks with Recurrent Generative Feedback
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #938
COT-GAN: Generating Sequential Data via Causal Optimal Transport
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #939
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #940
Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #941
Implicit Rank-Minimizing Autoencoder
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #942
Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #943
Set2Graph: Learning Graphs From Sets
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #944
Efficient Generation of Structured Objects with Constrained Adversarial Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #945
Improving GAN Training with Probability Ratio Clipping and Sample Reweighting
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #946
Regularized linear autoencoders recover the principal components, eventually
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #947
BoxE: A Box Embedding Model for Knowledge Base Completion
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #948
BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #949
Learning Object-Centric Representations of Multi-Object Scenes from Multiple Views
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #950
Deep Statistical Solvers
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #951
Learning of Discrete Graphical Models with Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #952
Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #953
Falcon: Fast Spectral Inference on Encrypted Data
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #954
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #955
Learning Composable Energy Surrogates for PDE Order Reduction
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #956
AvE: Assistance via Empowerment
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #957
EcoLight: Intersection Control in Developing Regions Under Extreme Budget and Network Constraints
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #958
RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #959
Barking up the right tree: an approach to search over molecule synthesis DAGs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #960
Synthesizing Tasks for Block-based Programming
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #961
Deep Imitation Learning for Bimanual Robotic Manipulation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #962
PRANK: motion Prediction based on RANKing
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #963
Meta-trained agents implement Bayes-optimal agents
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #964
On the equivalence of molecular graph convolution and molecular wave function with poor basis set
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #965
Dynamic allocation of limited memory resources in reinforcement learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #966
Ensembling geophysical models with Bayesian Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #967
Neurosymbolic Transformers for Multi-Agent Communication
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #968
Avoiding Side Effects By Considering Future Tasks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #969
What Did You Think Would Happen? Explaining Agent Behaviour through Intended Outcomes
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #970
Sequence to Multi-Sequence Learning via Conditional Chain Mapping for Mixture Signals
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #971
Learning Mutational Semantics
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #972
Zero-Resource Knowledge-Grounded Dialogue Generation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #973
Representation Learning for Integrating Multi-domain Outcomes to Optimize Individualized Treatment
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #974
Causal analysis of Covid-19 Spread in Germany
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #975
Dynamic Fusion of Eye Movement Data and Verbal Narrations in Knowledge-rich Domains
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #976
X-CAL: Explicit Calibration for Survival Analysis
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #977
Experimental design for MRI by greedy policy search
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #978
How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #979
OrganITE: Optimal transplant donor organ offering using an individual treatment effect
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #980
When Counterpoint Meets Chinese Folk Melodies
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #981
BERT Loses Patience: Fast and Robust Inference with Early Exit
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #982
Unsupervised Text Generation by Learning from Search
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #983
Leap-Of-Thought: Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #984
A Spectral Energy Distance for Parallel Speech Synthesis
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #985
Compositional Generalization by Learning Analytical Expressions
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #986
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #987
Kernel Alignment Risk Estimator: Risk Prediction from Training Data
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #988
Fourier Sparse Leverage Scores and Approximate Kernel Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #989
Demystifying Orthogonal Monte Carlo and Beyond
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #990
Unfolding recurrence by Green’s functions for optimized reservoir computing
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #991
A Group-Theoretic Framework for Data Augmentation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #992
Understanding Double Descent Requires A Fine-Grained Bias-Variance Decomposition
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #993
Triple descent and the two kinds of overfitting: where & why do they appear?
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #994
The interplay between randomness and structure during learning in RNNs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #995
A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #996
When Do Neural Networks Outperform Kernel Methods?
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #997
The Statistical Cost of Robust Kernel Hyperparameter Turning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #998
Asymptotic normality and confidence intervals for derivatives of 2-layers neural network in the random features model
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #999
Randomized tests for high-dimensional regression: A more efficient and powerful solution
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1000
Sample complexity and effective dimension for regression on manifolds
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1001
An analytic theory of shallow networks dynamics for hinge loss classification
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1002
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1003
One-bit Supervision for Image Classification
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1004
Your Classifier can Secretly Suffice Multi-Source Domain Adaptation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1005
Early-Learning Regularization Prevents Memorization of Noisy Labels
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1006
Compositional Zero-Shot Learning via Fine-Grained Dense Feature Composition
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1007
Universal Domain Adaptation through Self Supervision
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1008
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1009
A causal view of compositional zero-shot recognition
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1010
CompRess: Self-Supervised Learning by Compressing Representations
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1011
Big Self-Supervised Models are Strong Semi-Supervised Learners
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1012
Provably Consistent Partial-Label Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1013
Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1014
Unsupervised Translation of Programming Languages
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1015
Uncertainty-aware Self-training for Few-shot Text Classification
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1016
Discriminative Sounding Objects Localization via Self-supervised Audiovisual Matching
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1017
Teaching a GAN What Not to Learn
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1018
A Randomized Algorithm to Reduce the Support of Discrete Measures
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1019
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1021
Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1022
Better Full-Matrix Regret via Parameter-Free Online Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1023
Locally-Adaptive Nonparametric Online Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1024
Online Learning with Primary and Secondary Losses
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1025
Online Linear Optimization with Many Hints
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1026
Exploiting the Surrogate Gap in Online Multiclass Classification
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1027
Temporal Variability in Implicit Online Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1028
Prediction with Corrupted Expert Advice
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1029
A mathematical model for automatic differentiation in machine learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1030
Online Non-Convex Optimization with Imperfect Feedback
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1031
Adaptive Importance Sampling for Finite-Sum Optimization and Sampling with Decreasing Step-Sizes
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1032
Differentially-Private Federated Linear Bandits
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1033
Learning Strategy-Aware Linear Classifiers
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1034
BRP-NAS: Prediction-based NAS using GCNs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1035
Neural Architecture Generator Optimization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1036
Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1037
AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1038
Agnostic Learning with Multiple Objectives
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1039
Training Stronger Baselines for Learning to Optimize
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1040
GPU-Accelerated Primal Learning for Extremely Fast Large-Scale Classification
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1041
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1042
Geometric Dataset Distances via Optimal Transport
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1043
Efficient Algorithms for Device Placement of DNN Graph Operators
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1044
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1045
Bayesian Optimization for Iterative Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1046
Model Selection for Production System via Automated Online Experiments
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1047
Interpretable and Personalized Apprenticeship Scheduling: Learning Interpretable Scheduling Policies from Heterogeneous User Demonstrations
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1048
CryptoNAS: Private Inference on a ReLU Budget
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1050
Diversity-Guided Multi-Objective Bayesian Optimization With Batch Evaluations
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1051
High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1052
Learning Feature Sparse Principal Subspace
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1053
Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust Support Vector Machine
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1054
Stochastic Optimization with Laggard Data Pipelines
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1055
Black-Box Optimization with Local Generative Surrogates
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1056
Learning Linear Programs from Optimal Decisions
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1057
Acceleration with a Ball Optimization Oracle
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1058
Convex optimization based on global lower second-order models
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1059
Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1060
Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1061
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1062
An efficient nonconvex reformulation of stagewise convex optimization problems
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1063
Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1064
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1065
First-Order Methods for Large-Scale Market Equilibrium Computation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1066
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1067
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1068
Deep Smoothing of the Implied Volatility Surface
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1069
What went wrong and when? Instance-wise feature importance for time-series black-box models
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1070
Learning from Failure: De-biasing Classifier from Biased Classifier
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1071
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1072
Learning Global Transparent Models consistent with Local Contrastive Explanations
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1073
Towards Safe Policy Improvement for Non-Stationary MDPs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1074
Decisions, Counterfactual Explanations and Strategic Behavior
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1075
From Predictions to Decisions: Using Lookahead Regularization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1076
Model Agnostic Multilevel Explanations
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1077
Achieving Equalized Odds by Resampling Sensitive Attributes
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1078
Regularizing Black-box Models for Improved Interpretability
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1079
Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1080
MetaPoison: Practical General-purpose Clean-label Data Poisoning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1081
Understanding Gradient Clipping in Private SGD: A Geometric Perspective
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1082
Coresets via Bilevel Optimization for Continual Learning and Streaming
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1083
Linear Dynamical Systems as a Core Computational Primitive
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1084
BanditPAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1085
Sliding Window Algorithms for k-Clustering Problems
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1086
Fast and Accurate $k$-means++ via Rejection Sampling
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1087
NeuMiss networks: differentiable programming for supervised learning with missing values.
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1088
Debiasing Averaged Stochastic Gradient Descent to handle missing values
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1089
Coresets for Near-Convex Functions
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1091
HiPPO: Recurrent Memory with Optimal Polynomial Projections
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1092
Online MAP Inference of Determinantal Point Processes
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1093
Joints in Random Forests
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1094
Approximate Cross-Validation for Structured Models
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1095
A convex optimization formulation for multivariate regression
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1096
Adaptive Reduced Rank Regression
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1097
Self-Distillation Amplifies Regularization in Hilbert Space
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1098
Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? --- A Neural Tangent Kernel Perspective
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1099
Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1100
Explicit Regularisation in Gaussian Noise Injections
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1101
Rational neural networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1102
On the Similarity between the Laplace and Neural Tangent Kernels
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1103
Neural Anisotropy Directions
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1105
Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local Elasticity
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1106
Limits to Depth Efficiencies of Self-Attention
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1107
On the linearity of large non-linear models: when and why the tangent kernel is constant
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1108
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1109
Directional Pruning of Deep Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1110
Winning the Lottery with Continuous Sparsification
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1111
Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1112
On the universality of deep learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1113
Reservoir Computing meets Recurrent Kernels and Structured Transforms
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1114
The Diversified Ensemble Neural Network
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1115
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1116
Spin-Weighted Spherical CNNs
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1117
Autoencoders that don't overfit towards the Identity
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1118
Modern Hopfield Networks and Attention for Immune Repertoire Classification
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1119
UCSG-NET- Unsupervised Discovering of Constructive Solid Geometry Tree
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1120
UCLID-Net: Single View Reconstruction in Object Space
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1121
Graph Geometry Interaction Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1122
Feature Importance Ranking for Deep Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1123
Introducing Routing Uncertainty in Capsule Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1124
The Pitfalls of Simplicity Bias in Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1125
Primal-Dual Mesh Convolutional Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1126
The Convolution Exponential and Generalized Sylvester Flows
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1127
Coherent Hierarchical Multi-Label Classification Networks
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1128
Differentiable Top-k with Optimal Transport
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1129
Proximal Mapping for Deep Regularization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1130
CSER: Communication-efficient SGD with Error Reset
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1131
Practical Low-Rank Communication Compression in Decentralized Deep Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1132
A Decentralized Parallel Algorithm for Training Generative Adversarial Nets
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1133
Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1134
Distributed Newton Can Communicate Less and Resist Byzantine Workers
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1135
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1136
Dual-Free Stochastic Decentralized Optimization with Variance Reduction
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1137
FedSplit: an algorithmic framework for fast federated optimization
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1138
Distributionally Robust Federated Averaging
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1139
Personalized Federated Learning with Moreau Envelopes
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1140
Minibatch vs Local SGD for Heterogeneous Distributed Learning
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1141
Minibatch Stochastic Approximate Proximal Point Methods
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1142
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1143
A Simple and Efficient Smoothing Method for Faster Optimization and Local Exploration
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1144
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1145
Linearly Converging Error Compensated SGD
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1253
The All-or-Nothing Phenomenon in Sparse Tensor PCA
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1366
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1787
ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1789
Normalizing Kalman Filters for Multivariate Time Series Analysis
[ Paper ]
Poster
Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #1811
Learning Augmented Energy Minimization via Speed Scaling
[ Paper ]
Memorial
Wed Dec 09 11:00 AM -- 12:00 PM (PST)
In Memory of Olivier Chapelle
Symposium
Wed Dec 09 12:00 PM -- 04:00 PM (PST)
COVID-19 Symposium Day 2
Tutorial
Wed Dec 09 12:00 PM -- 12:50 PM (PST)
(Track2) Practical Uncertainty Estimation and Out-of-Distribution Robustness in Deep Learning Q&A
Tutorial
Wed Dec 09 02:00 PM -- 02:50 PM (PST)
(Track1) Abstraction & Reasoning in AI systems: Modern Perspectives Q&A
Invited Talk
Wed Dec 09 05:00 PM -- 07:00 PM (PST)
A Future of Work for the Invisible Workers in A.I.
Oral
Wed Dec 09 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Vision Applications
Learning Implicit Functions for Topology-Varying Dense 3D Shape Correspondence
[ Paper ]
Oral
Wed Dec 09 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Graph/Meta Learning/Software
FrugalML: How to use ML Prediction APIs more accurately and cheaply
[ Paper ]
Oral
Wed Dec 09 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Learning Theory
Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method
[ Paper ]
Oral
Wed Dec 09 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Vision Applications
LoopReg: Self-supervised Learning of Implicit Surface Correspondences, Pose and Shape for 3D Human Mesh Registration
[ Paper ]
Oral
Wed Dec 09 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Graph/Meta Learning/Software
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
[ Paper ]
Oral
Wed Dec 09 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Learning Theory
Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs
[ Paper ]
Oral
Wed Dec 09 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Vision Applications
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks
[ Paper ]
Oral
Wed Dec 09 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Graph/Meta Learning/Software
PyGlove: Symbolic Programming for Automated Machine Learning
[ Paper ]
Oral
Wed Dec 09 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Learning Theory
Worst-Case Analysis for Randomly Collected Data
[ Paper ]
Break
Wed Dec 09 06:45 PM -- 07:00 PM (PST)
Break
Break
Wed Dec 09 06:45 PM -- 07:00 PM (PST)
Break
Spotlight
Wed Dec 09 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Vision Applications
Distribution Matching for Crowd Counting
[ Paper ]
Spotlight
Wed Dec 09 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Graph/Meta Learning/Software
Improved Schemes for Episodic Memory-based Lifelong Learning
[ Paper ]
Spotlight
Wed Dec 09 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Learning Theory
On Adaptive Distance Estimation
[ Paper ]
Spotlight
Wed Dec 09 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Vision Applications
Texture Interpolation for Probing Visual Perception
[ Paper ]
Spotlight
Wed Dec 09 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Graph/Meta Learning/Software
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
[ Paper ]
Spotlight
Wed Dec 09 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Learning Theory
Tight First- and Second-Order Regret Bounds for Adversarial Linear Bandits
[ Paper ]
Spotlight
Wed Dec 09 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Vision Applications
Consistent Structural Relation Learning for Zero-Shot Segmentation
[ Paper ]
Spotlight
Wed Dec 09 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Graph/Meta Learning/Software
Uncertainty Aware Semi-Supervised Learning on Graph Data
[ Paper ]
Spotlight
Wed Dec 09 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Learning Theory
Delay and Cooperation in Nonstochastic Linear Bandits
[ Paper ]
Spotlight
Wed Dec 09 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Vision Applications
CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations
[ Paper ]
Spotlight
Wed Dec 09 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Graph/Meta Learning/Software
Rethinking Importance Weighting for Deep Learning under Distribution Shift
[ Paper ]
Spotlight
Wed Dec 09 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Learning Theory
Unreasonable Effectiveness of Greedy Algorithms in Multi-Armed Bandit with Many Arms
[ Paper ]
Q&A
Wed Dec 09 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Wed Dec 09 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Wed Dec 09 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Vision Applications
ShapeFlow: Learnable Deformation Flows Among 3D Shapes
[ Paper ]
Spotlight
Wed Dec 09 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Graph/Meta Learning/Software
Modular Meta-Learning with Shrinkage
[ Paper ]
Spotlight
Wed Dec 09 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Learning Theory
Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition
[ Paper ]
Spotlight
Wed Dec 09 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Vision Applications
Neural Mesh Flow: 3D Manifold Mesh Generation via Diffeomorphic Flows
[ Paper ]
Spotlight
Wed Dec 09 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Graph/Meta Learning/Software
JAX MD: A Framework for Differentiable Physics
[ Paper ]
Spotlight
Wed Dec 09 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Learning Theory
A Tight Lower Bound and Efficient Reduction for Swap Regret
[ Paper ]
Spotlight
Wed Dec 09 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Vision Applications
Counterfactual Vision-and-Language Navigation: Unravelling the Unseen
[ Paper ]
Spotlight
Wed Dec 09 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Graph/Meta Learning/Software
RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference
[ Paper ]
Spotlight
Wed Dec 09 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Learning Theory
Estimation of Skill Distribution from a Tournament
[ Paper ]
Q&A
Wed Dec 09 08:20 PM -- 08:30 PM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Wed Dec 09 08:20 PM -- 08:30 PM (PST) @ Orals & Spotlights: Vision Applications
RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder
[ Paper ]
Spotlight
Wed Dec 09 08:20 PM -- 08:30 PM (PST) @ Orals & Spotlights: Learning Theory
Optimal Prediction of the Number of Unseen Species with Multiplicity
[ Paper ]
Break
Wed Dec 09 08:30 PM -- 09:00 PM (PST)
Break
Q&A
Wed Dec 09 08:30 PM -- 08:40 PM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Wed Dec 09 08:30 PM -- 08:40 PM (PST) @ Orals & Spotlights: Learning Theory
Estimating Rank-One Spikes from Heavy-Tailed Noise via Self-Avoiding Walks
[ Paper ]
Break
Wed Dec 09 08:40 PM -- 09:00 PM (PST)
Break
Q&A
Wed Dec 09 08:40 PM -- 08:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1147
Consistent Structural Relation Learning for Zero-Shot Segmentation
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1148
TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1149
AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1150
UnModNet: Learning to Unwrap a Modulo Image for High Dynamic Range Imaging
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1151
Group Contextual Encoding for 3D Point Clouds
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1152
Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1153
Dual-Resolution Correspondence Networks
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1154
Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1155
Modeling Noisy Annotations for Crowd Counting
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1156
RSKDD-Net: Random Sample-based Keypoint Detector and Descriptor
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1157
Distribution Matching for Crowd Counting
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1158
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1159
Every View Counts: Cross-View Consistency in 3D Object Detection with Hybrid-Cylindrical-Spherical Voxelization
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1160
RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1161
Structured Convolutions for Efficient Neural Network Design
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1162
Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1164
MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1165
Ultrahyperbolic Representation Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1166
Reparameterizing Mirror Descent as Gradient Descent
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1167
Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1168
Handling Missing Data with Graph Representation Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1169
Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1170
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1171
Timeseries Anomaly Detection using Temporal Hierarchical One-Class Network
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1172
How Can I Explain This to You? An Empirical Study of Deep Neural Network Explanation Methods
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1173
PEP: Parameter Ensembling by Perturbation
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1174
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1175
Unifying Activation- and Timing-based Learning Rules for Spiking Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1176
Dirichlet Graph Variational Autoencoder
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1177
Gradient Boosted Normalizing Flows
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1178
Improved Guarantees for k-means++ and k-means++ Parallel
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1179
Estimation of Skill Distribution from a Tournament
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1180
Transfer Learning via $\ell_1$ Regularization
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1181
Robust Meta-learning for Mixed Linear Regression with Small Batches
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1182
Efficient Projection-free Algorithms for Saddle Point Problems
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1183
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1184
A Fair Classifier Using Kernel Density Estimation
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1185
List-Decodable Mean Estimation via Iterative Multi-Filtering
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1186
On Learning Ising Models under Huber's Contamination Model
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1187
Worst-Case Analysis for Randomly Collected Data
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1188
Extrapolation Towards Imaginary 0-Nearest Neighbour and Its Improved Convergence Rate
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1189
A General Method for Robust Learning from Batches
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1191
Optimal Prediction of the Number of Unseen Species with Multiplicity
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1192
Probabilistic Active Meta-Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1193
Meta-Consolidation for Continual Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1194
Understanding the Role of Training Regimes in Continual Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1195
Supermasks in Superposition
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1196
Improved Schemes for Episodic Memory-based Lifelong Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1197
Continual Learning with Node-Importance based Adaptive Group Sparse Regularization
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1198
GAN Memory with No Forgetting
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1199
Meta-Learning with Adaptive Hyperparameters
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1200
Online Structured Meta-learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1201
Modeling and Optimization Trade-off in Meta-learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1202
Structured Prediction for Conditional Meta-Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1203
Meta-learning from Tasks with Heterogeneous Attribute Spaces
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1204
Gradient-EM Bayesian Meta-Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1205
MATE: Plugging in Model Awareness to Task Embedding for Meta Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1206
Neural Complexity Measures
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1207
Modular Meta-Learning with Shrinkage
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1208
Gradient Surgery for Multi-Task Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1209
Organizing recurrent network dynamics by task-computation to enable continual learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1210
Finding the Homology of Decision Boundaries with Active Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1211
Exemplar Guided Active Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1212
OOD-MAML: Meta-Learning for Few-Shot Out-of-Distribution Detection and Classification
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1213
An Unbiased Risk Estimator for Learning with Augmented Classes
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1214
Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1215
Rethinking Importance Weighting for Deep Learning under Distribution Shift
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1216
Robust Correction of Sampling Bias using Cumulative Distribution Functions
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1217
Learning from Positive and Unlabeled Data with Arbitrary Positive Shift
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1218
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1219
A Variational Approach for Learning from Positive and Unlabeled Data
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1220
HRN: A Holistic Approach to One Class Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1221
Rethinking the Value of Labels for Improving Class-Imbalanced Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1222
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1223
Learning from Aggregate Observations
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1224
Self-training Avoids Using Spurious Features Under Domain Shift
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1225
Learning Physical Constraints with Neural Projections
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1226
Time-Reversal Symmetric ODE Network
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1227
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1228
Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor Networks
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1229
LoopReg: Self-supervised Learning of Implicit Surface Correspondences, Pose and Shape for 3D Human Mesh Registration
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1230
Adaptive Learning of Rank-One Models for Efficient Pairwise Sequence Alignment
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1231
Fourier-transform-based attribution priors improve the interpretability and stability of deep learning models for genomics
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1232
Counterfactual Vision-and-Language Navigation: Unravelling the Unseen
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1233
Neural FFTs for Universal Texture Image Synthesis
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1234
CodeCMR: Cross-Modal Retrieval For Function-Level Binary Source Code Matching
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1235
Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1236
EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1237
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1238
JAX MD: A Framework for Differentiable Physics
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1239
Multi-agent Trajectory Prediction with Fuzzy Query Attention
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1240
Learning Agent Representations for Ice Hockey
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1241
Correlation Robust Influence Maximization
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1242
On Adaptive Distance Estimation
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1243
Recovery of sparse linear classifiers from mixture of responses
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1244
Robustness of Community Detection to Random Geometric Perturbations
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1245
Entrywise convergence of iterative methods for eigenproblems
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1246
Optimal Iterative Sketching Methods with the Subsampled Randomized Hadamard Transform
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1247
Beyond Lazy Training for Over-parameterized Tensor Decomposition
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1248
Estimating Rank-One Spikes from Heavy-Tailed Noise via Self-Avoiding Walks
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1249
Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1250
Precise expressions for random projections: Low-rank approximation and randomized Newton
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1252
Matrix Completion with Hierarchical Graph Side Information
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1254
A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1255
Fairness constraints can help exact inference in structured prediction
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1256
Exact expressions for double descent and implicit regularization via surrogate random design
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1257
SURF: A Simple, Universal, Robust, Fast Distribution Learning Algorithm
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1258
Uncertainty Aware Semi-Supervised Learning on Graph Data
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1259
Calibrated Reliable Regression using Maximum Mean Discrepancy
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1260
Energy-based Out-of-distribution Detection
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1261
Neural Manifold Ordinary Differential Equations
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1262
NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1263
Adaptation Properties Allow Identification of Optimized Neural Codes
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1264
Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1265
Learning to search efficiently for causally near-optimal treatments
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1266
General Control Functions for Causal Effect Estimation from IVs
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1267
Characterizing Optimal Mixed Policies: Where to Intervene and What to Observe
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1268
Active Structure Learning of Causal DAGs via Directed Clique Trees
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1269
Adaptive Experimental Design with Temporal Interference: A Maximum Likelihood Approach
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1270
Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1271
Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization Method
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1272
Evaluating and Rewarding Teamwork Using Cooperative Game Abstractions
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1273
Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1274
Unreasonable Effectiveness of Greedy Algorithms in Multi-Armed Bandit with Many Arms
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1275
Batched Coarse Ranking in Multi-Armed Bandits
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1276
Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1277
Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1278
Stage-wise Conservative Linear Bandits
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1279
Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1280
Tight First- and Second-Order Regret Bounds for Adversarial Linear Bandits
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1281
Delay and Cooperation in Nonstochastic Linear Bandits
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1282
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1283
Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1284
Dynamic Regret of Convex and Smooth Functions
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1285
Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1286
Online learning with dynamics: A minimax perspective
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1287
A Tight Lower Bound and Efficient Reduction for Swap Regret
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1288
Making Non-Stochastic Control (Almost) as Easy as Stochastic
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1289
Non-Stochastic Control with Bandit Feedback
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1290
Learning Implicit Functions for Topology-Varying Dense 3D Shape Correspondence
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1291
Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1292
Geo-PIFu: Geometry and Pixel Aligned Implicit Functions for Single-view Human Reconstruction
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1293
Generative 3D Part Assembly via Dynamic Graph Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1294
Online Adaptation for Consistent Mesh Reconstruction in the Wild
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1295
Learning Deformable Tetrahedral Meshes for 3D Reconstruction
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1296
Weakly Supervised Deep Functional Maps for Shape Matching
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1297
Neural Star Domain as Primitive Representation
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1298
Robust Multi-Object Matching via Iterative Reweighting of the Graph Connection Laplacian
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1299
Grasp Proposal Networks: An End-to-End Solution for Visual Learning of Robotic Grasps
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1300
CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1301
ShapeFlow: Learnable Deformation Flows Among 3D Shapes
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1302
Neural Mesh Flow: 3D Manifold Mesh Generation via Diffeomorphic Flows
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1303
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1304
Texture Interpolation for Probing Visual Perception
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1305
Byzantine Resilient Distributed Multi-Task Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1306
FrugalML: How to use ML Prediction APIs more accurately and cheaply
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1307
Improving Auto-Augment via Augmentation-Wise Weight Sharing
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1308
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1309
RandAugment: Practical Automated Data Augmentation with a Reduced Search Space
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1311
A Closer Look at the Training Strategy for Modern Meta-Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1312
Transferable Calibration with Lower Bias and Variance in Domain Adaptation
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1313
Unsupervised Learning of Object Landmarks via Self-Training Correspondence
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1314
Autofocused oracles for model-based design
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1315
Hierarchical Neural Architecture Search for Deep Stereo Matching
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1316
UWSOD: Toward Fully-Supervised-Level Capacity Weakly Supervised Object Detection
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1317
Hierarchical Granularity Transfer Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1318
PyGlove: Symbolic Programming for Automated Machine Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1319
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1321
RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1322
TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning
[ Paper ]
Poster
Wed Dec 09 09:00 PM -- 11:00 PM (PST) @ Poster Session 4 #1723
Distributed Distillation for On-Device Learning
[ Paper ]
Tutorial
Thu Dec 10 12:00 AM -- 12:50 AM (PST)
(Track2) Deep Conversational AI Q&A
Tutorial
Thu Dec 10 02:00 AM -- 02:50 AM (PST)
(Track3) Designing Learning Dynamics Q&A
Tutorial
Thu Dec 10 03:00 AM -- 03:50 AM (PST)
(Track3) Deep Implicit Layers: Neural ODEs, Equilibrium Models, and Differentiable Optimization Q&A
Town Hall
Thu Dec 10 04:00 AM -- 05:00 AM & Thu Dec 10 04:00 PM -- 05:00 PM (PST)
NeurIPS Town Hall
Invited Talk (Breiman Lecture)
Thu Dec 10 05:00 AM -- 07:00 AM (PST)
Causal Learning
Oral
Thu Dec 10 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification
[ Paper ]
Oral
Thu Dec 10 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Graph/Relational/Theory
Graph Cross Networks with Vertex Infomax Pooling
[ Paper ]
Oral
Thu Dec 10 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
Contrastive learning of global and local features for medical image segmentation with limited annotations
[ Paper ]
Oral
Thu Dec 10 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Deep Learning
A shooting formulation of deep learning
[ Paper ]
Oral
Thu Dec 10 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Neuroscience
Learning abstract structure for drawing by efficient motor program induction
[ Paper ]
Oral
Thu Dec 10 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Optimization/Theory
Black-Box Ripper: Copying black-box models using generative evolutionary algorithms
[ Paper ]
Oral
Thu Dec 10 06:00 AM -- 06:15 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Robust-Adaptive Control of Linear Systems: beyond Quadratic Costs
[ Paper ]
Oral
Thu Dec 10 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Fast and Flexible Temporal Point Processes with Triangular Maps
[ Paper ]
Oral
Thu Dec 10 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Graph/Relational/Theory
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs
[ Paper ]
Oral
Thu Dec 10 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning
[ Paper ]
Oral
Thu Dec 10 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Deep Learning
On the training dynamics of deep networks with $L_2$ regularization
[ Paper ]
Oral
Thu Dec 10 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Neuroscience
Non-reversible Gaussian processes for identifying latent dynamical structure in neural data
[ Paper ]
Oral
Thu Dec 10 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Optimization/Theory
Towards a Better Global Loss Landscape of GANs
[ Paper ]
Oral
Thu Dec 10 06:15 AM -- 06:30 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Self-Paced Deep Reinforcement Learning
[ Paper ]
Oral
Thu Dec 10 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Greedy inference with structure-exploiting lazy maps
[ Paper ]
Oral
Thu Dec 10 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Graph/Relational/Theory
Graph Random Neural Networks for Semi-Supervised Learning on Graphs
[ Paper ]
Oral
Thu Dec 10 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows
[ Paper ]
Oral
Thu Dec 10 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Deep Learning
Compositional Explanations of Neurons
[ Paper ]
Oral
Thu Dec 10 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Neuroscience
Gibbs Sampling with People
[ Paper ]
Oral
Thu Dec 10 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Optimization/Theory
Online Sinkhorn: Optimal Transport distances from sample streams
[ Paper ]
Oral
Thu Dec 10 06:30 AM -- 06:45 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning
[ Paper ]
Break
Thu Dec 10 06:45 AM -- 07:00 AM (PST)
Break
Break
Thu Dec 10 06:45 AM -- 07:00 AM (PST)
Break
Break
Thu Dec 10 06:45 AM -- 07:00 AM (PST)
Break
Break
Thu Dec 10 06:45 AM -- 07:00 AM (PST)
Break
Break
Thu Dec 10 06:45 AM -- 07:00 AM (PST)
Break
Spotlight
Thu Dec 10 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Sampling from a k-DPP without looking at all items
[ Paper ]
Spotlight
Thu Dec 10 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Graph/Relational/Theory
Learning Graph Structure With A Finite-State Automaton Layer
[ Paper ]
Spotlight
Thu Dec 10 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
Self-Supervised Relational Reasoning for Representation Learning
[ Paper ]
Spotlight
Thu Dec 10 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Deep Learning
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints
[ Paper ]
Spotlight
Thu Dec 10 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Neuroscience
Stable and expressive recurrent vision models
[ Paper ]
Spotlight
Thu Dec 10 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Optimization/Theory
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
[ Paper ]
Spotlight
Thu Dec 10 07:00 AM -- 07:10 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Bandit Linear Control
[ Paper ]
Spotlight
Thu Dec 10 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Non-parametric Models for Non-negative Functions
[ Paper ]
Spotlight
Thu Dec 10 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Graph/Relational/Theory
Pointer Graph Networks
[ Paper ]
Spotlight
Thu Dec 10 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
Object-Centric Learning with Slot Attention
[ Paper ]
Spotlight
Thu Dec 10 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Deep Learning
On Power Laws in Deep Ensembles
[ Paper ]
Spotlight
Thu Dec 10 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Neuroscience
Identifying Learning Rules From Neural Network Observables
[ Paper ]
Spotlight
Thu Dec 10 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Optimization/Theory
Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions
[ Paper ]
Spotlight
Thu Dec 10 07:10 AM -- 07:20 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Neural Dynamic Policies for End-to-End Sensorimotor Learning
[ Paper ]
Q&A
Thu Dec 10 07:20 AM -- 07:30 AM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Thu Dec 10 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Distribution-free binary classification: prediction sets, confidence intervals and calibration
[ Paper ]
Spotlight
Thu Dec 10 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
Telescoping Density-Ratio Estimation
[ Paper ]
Spotlight
Thu Dec 10 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Deep Learning
Learning the Geometry of Wave-Based Imaging
[ Paper ]
Spotlight
Thu Dec 10 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Neuroscience
A new inference approach for training shallow and deep generalized linear models of noisy interacting neurons
[ Paper ]
Spotlight
Thu Dec 10 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Optimization/Theory
Conformal Symplectic and Relativistic Optimization
[ Paper ]
Spotlight
Thu Dec 10 07:20 AM -- 07:30 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Effective Diversity in Population Based Reinforcement Learning
[ Paper ]
Spotlight
Thu Dec 10 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Factor Graph Grammars
[ Paper ]
Spotlight
Thu Dec 10 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Graph/Relational/Theory
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks
[ Paper ]
Spotlight
Thu Dec 10 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations
[ Paper ]
Spotlight
Thu Dec 10 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Deep Learning
The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks
[ Paper ]
Spotlight
Thu Dec 10 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Neuroscience
Modeling Shared responses in Neuroimaging Studies through MultiView ICA
[ Paper ]
Spotlight
Thu Dec 10 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Optimization/Theory
Random Reshuffling is Not Always Better
[ Paper ]
Spotlight
Thu Dec 10 07:30 AM -- 07:40 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
[ Paper ]
Q&A
Thu Dec 10 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
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Thu Dec 10 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
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Thu Dec 10 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
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Thu Dec 10 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
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Thu Dec 10 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
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Thu Dec 10 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Thu Dec 10 07:40 AM -- 07:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Thu Dec 10 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Asymptotically Optimal Exact Minibatch Metropolis-Hastings
[ Paper ]
Spotlight
Thu Dec 10 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Graph/Relational/Theory
Convergence and Stability of Graph Convolutional Networks on Large Random Graphs
[ Paper ]
Spotlight
Thu Dec 10 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks
[ Paper ]
Spotlight
Thu Dec 10 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Deep Learning
Sparse and Continuous Attention Mechanisms
[ Paper ]
Spotlight
Thu Dec 10 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Neuroscience
Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning
[ Paper ]
Spotlight
Thu Dec 10 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Optimization/Theory
The Statistical Complexity of Early-Stopped Mirror Descent
[ Paper ]
Spotlight
Thu Dec 10 07:50 AM -- 08:00 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Reward Propagation Using Graph Convolutional Networks
[ Paper ]
Spotlight
Thu Dec 10 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Bayes Consistency vs. H-Consistency: The Interplay between Surrogate Loss Functions and the Scoring Function Class
[ Paper ]
Spotlight
Thu Dec 10 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Graph/Relational/Theory
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
[ Paper ]
Spotlight
Thu Dec 10 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
Stochastic Normalizing Flows
[ Paper ]
Spotlight
Thu Dec 10 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Deep Learning
Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks
[ Paper ]
Spotlight
Thu Dec 10 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Neuroscience
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence
[ Paper ]
Spotlight
Thu Dec 10 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Optimization/Theory
Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree
[ Paper ]
Spotlight
Thu Dec 10 08:00 AM -- 08:10 AM (PST) @ Orals & Spotlights: Reinforcement Learning
On the Convergence of Smooth Regularized Approximate Value Iteration Schemes
[ Paper ]
Spotlight
Thu Dec 10 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Confidence sequences for sampling without replacement
[ Paper ]
Spotlight
Thu Dec 10 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Graph/Relational/Theory
Most ReLU Networks Suffer from $\ell^2$ Adversarial Perturbations
[ Paper ]
Spotlight
Thu Dec 10 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
Generative Neurosymbolic Machines
[ Paper ]
Spotlight
Thu Dec 10 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Deep Learning
Directional convergence and alignment in deep learning
[ Paper ]
Spotlight
Thu Dec 10 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Neuroscience
System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina
[ Paper ]
Spotlight
Thu Dec 10 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Optimization/Theory
Towards Problem-dependent Optimal Learning Rates
[ Paper ]
Spotlight
Thu Dec 10 08:10 AM -- 08:20 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Latent World Models For Intrinsically Motivated Exploration
[ Paper ]
Spotlight
Thu Dec 10 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Statistical and Topological Properties of Sliced Probability Divergences
[ Paper ]
Spotlight
Thu Dec 10 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Graph/Relational/Theory
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples
[ Paper ]
Spotlight
Thu Dec 10 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Unsupervised/Probabilistic
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks
[ Paper ]
Spotlight
Thu Dec 10 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Deep Learning
Neural Controlled Differential Equations for Irregular Time Series
[ Paper ]
Spotlight
Thu Dec 10 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Neuroscience
A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network
[ Paper ]
Spotlight
Thu Dec 10 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Optimization/Theory
On Uniform Convergence and Low-Norm Interpolation Learning
[ Paper ]
Spotlight
Thu Dec 10 08:20 AM -- 08:30 AM (PST) @ Orals & Spotlights: Reinforcement Learning
Learning to Play No-Press Diplomacy with Best Response Policy Iteration
[ Paper ]
Q&A
Thu Dec 10 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Thu Dec 10 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
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Thu Dec 10 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
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Thu Dec 10 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
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Thu Dec 10 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Thu Dec 10 08:30 AM -- 08:40 AM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Thu Dec 10 08:30 AM -- 08:40 AM (PST) @ Orals & Spotlights: Probabilistic Models/Statistics
Testing Determinantal Point Processes
[ Paper ]
Break
Thu Dec 10 08:40 AM -- 09:00 AM (PST)
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Thu Dec 10 08:40 AM -- 09:00 AM (PST)
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Thu Dec 10 08:40 AM -- 09:00 AM (PST)
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Thu Dec 10 08:40 AM -- 09:00 AM (PST)
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Q&A
Thu Dec 10 08:40 AM -- 08:50 AM (PST)
Joint Q&A for Preceeding Spotlights
Break
Thu Dec 10 08:50 AM -- 09:00 AM (PST)
Break
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #104
Unsupervised Sound Separation Using Mixture Invariant Training
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #188
Neural Networks with Small Weights and Depth-Separation Barriers
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #298
The Implications of Local Correlation on Learning Some Deep Functions
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #506
Provably adaptive reinforcement learning in metric spaces
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #518
Instance Based Approximations to Profile Maximum Likelihood
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #607
Continual Learning of Control Primitives : Skill Discovery via Reset-Games
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1323
Unsupervised Semantic Aggregation and Deformable Template Matching for Semi-Supervised Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1324
Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1325
Transductive Information Maximization for Few-Shot Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1326
Meta-Learning Requires Meta-Augmentation
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1327
Co-Tuning for Transfer Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1328
What Makes for Good Views for Contrastive Learning?
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1329
Self-Supervised Relational Reasoning for Representation Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1330
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1331
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1332
Supervised Contrastive Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1333
Curriculum Learning by Dynamic Instance Hardness
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1334
SuperLoss: A Generic Loss for Robust Curriculum Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1335
Neural Topographic Factor Analysis for fMRI Data
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1336
Self-supervised learning through the eyes of a child
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1337
Learnability with Indirect Supervision Signals
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1338
Learning from Label Proportions: A Mutual Contamination Framework
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1339
Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1340
Identifying signal and noise structure in neural population activity with Gaussian process factor models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1341
Neuronal Gaussian Process Regression
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1342
Estimating Fluctuations in Neural Representations of Uncertain Environments
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1343
Understanding spiking networks through convex optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1344
Factorized Neural Processes for Neural Processes: K-Shot Prediction of Neural Responses
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1345
Efficient estimation of neural tuning during naturalistic behavior
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1346
A new inference approach for training shallow and deep generalized linear models of noisy interacting neurons
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1347
Optimal Adaptive Electrode Selection to Maximize Simultaneously Recorded Neuron Yield
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1348
Non-reversible Gaussian processes for identifying latent dynamical structure in neural data
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1349
Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1350
Predictive coding in balanced neural networks with noise, chaos and delays
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1351
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1352
Online Neural Connectivity Estimation with Noisy Group Testing
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1353
Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1354
Rescuing neural spike train models from bad MLE
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1355
Flows for simultaneous manifold learning and density estimation
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1356
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1357
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1358
User-Dependent Neural Sequence Models for Continuous-Time Event Data
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1359
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1360
Hierarchical Quantized Autoencoders
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1361
Riemannian Continuous Normalizing Flows
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1362
Efficient Learning of Generative Models via Finite-Difference Score Matching
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1363
Learning Latent Space Energy-Based Prior Model
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1364
Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1365
VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1367
Stochastic Normalizing Flows
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1368
Generative Neurosymbolic Machines
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1369
Fast and Flexible Temporal Point Processes with Triangular Maps
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1370
Deep Rao-Blackwellised Particle Filters for Time Series Forecasting
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1371
Neural Dynamic Policies for End-to-End Sensorimotor Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1372
Critic Regularized Regression
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1373
Off-Policy Imitation Learning from Observations
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1374
Deep Inverse Q-learning with Constraints
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1375
Value-driven Hindsight Modelling
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1376
Effective Diversity in Population Based Reinforcement Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1377
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1378
Reward Propagation Using Graph Convolutional Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1379
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1380
Self-Paced Deep Reinforcement Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1381
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1382
Learning to Utilize Shaping Rewards: A New Approach of Reward Shaping
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1383
f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1384
Strictly Batch Imitation Learning by Energy-based Distribution Matching
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1385
Meta-Gradient Reinforcement Learning with an Objective Discovered Online
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1386
Inverse Reinforcement Learning from a Gradient-based Learner
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1387
Regret Bounds without Lipschitz Continuity: Online Learning with Relative-Lipschitz Losses
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1388
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1389
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1390
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1391
Exponential ergodicity of mirror-Langevin diffusions
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1392
Faster Wasserstein Distance Estimation with the Sinkhorn Divergence
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1393
Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1394
The Statistical Complexity of Early-Stopped Mirror Descent
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1395
Statistical and Topological Properties of Sliced Probability Divergences
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1396
Sharper Generalization Bounds for Pairwise Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1397
Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1398
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1399
Towards Problem-dependent Optimal Learning Rates
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1400
On Uniform Convergence and Low-Norm Interpolation Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1401
Estimating weighted areas under the ROC curve
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1402
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1403
On Second Order Behaviour in Augmented Neural ODEs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1404
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1405
Object-Centric Learning with Slot Attention
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1406
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1407
Probabilistic Time Series Forecasting with Shape and Temporal Diversity
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1408
A shooting formulation of deep learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1409
Training Linear Finite-State Machines
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1410
Benchmarking Deep Inverse Models over time, and the Neural-Adjoint method
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1411
Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1412
Fast Transformers with Clustered Attention
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1413
SMYRF - Efficient Attention using Asymmetric Clustering
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1414
Sparse and Continuous Attention Mechanisms
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1415
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1416
Denoising Diffusion Probabilistic Models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1417
Untangling tradeoffs between recurrence and self-attention in artificial neural networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1418
Neural Controlled Differential Equations for Irregular Time Series
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1419
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1420
Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1421
Pointer Graph Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1422
Can Graph Neural Networks Count Substructures?
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1423
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1424
Graph Random Neural Networks for Semi-Supervised Learning on Graphs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1425
Graph Contrastive Learning with Augmentations
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1426
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1427
Graph Stochastic Neural Networks for Semi-supervised Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1428
DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1429
SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1430
Curvature Regularization to Prevent Distortion in Graph Embedding
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1431
GCOMB: Learning Budget-constrained Combinatorial Algorithms over Billion-sized Graphs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1432
Subgraph Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1433
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1434
Factor Graph Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1435
WOR and $p$'s: Sketches for $\ell_p$-Sampling Without Replacement
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1436
Statistical Guarantees of Distributed Nearest Neighbor Classification
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1437
Robust Persistence Diagrams using Reproducing Kernels
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1438
Regression with reject option and application to kNN
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1439
A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1440
Uncertainty Quantification for Inferring Hawkes Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1441
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1442
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1443
A Stochastic Path Integral Differential EstimatoR Expectation Maximization Algorithm
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1444
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1445
Confidence sequences for sampling without replacement
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1446
Truthful Data Acquisition via Peer Prediction
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1447
Axioms for Learning from Pairwise Comparisons
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1448
Testing Determinantal Point Processes
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1449
Coded Sequential Matrix Multiplication For Straggler Mitigation
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1450
Functional Regularization for Representation Learning: A Unified Theoretical Perspective
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1451
Adaptive Sampling for Stochastic Risk-Averse Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1452
High-Dimensional Sparse Linear Bandits
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1453
Adversarial Bandits with Corruptions
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1454
On Regret with Multiple Best Arms
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1455
Model Selection in Contextual Stochastic Bandit Problems
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1456
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1457
Adapting to Misspecification in Contextual Bandits
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1458
Leveraging Predictions in Smoothed Online Convex Optimization via Gradient-based Algorithms
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1459
Bandit Linear Control
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1460
Robust-Adaptive Control of Linear Systems: beyond Quadratic Costs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1461
On the Convergence of Smooth Regularized Approximate Value Iteration Schemes
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1462
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1463
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1464
Implicit Distributional Reinforcement Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1465
Small Nash Equilibrium Certificates in Very Large Games
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1466
Contextual Games: Multi-Agent Learning with Side Information
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1467
Recursive Inference for Variational Autoencoders
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1468
Bayesian Pseudocoresets
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1469
Variational Bayesian Monte Carlo with Noisy Likelihoods
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1470
Bayesian Probabilistic Numerical Integration with Tree-Based Models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1471
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1472
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1473
Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1474
Decentralized Langevin Dynamics for Bayesian Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1475
Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1476
Decision-Making with Auto-Encoding Variational Bayes
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1477
Robust, Accurate Stochastic Optimization for Variational Inference
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1478
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1479
Efficient Low Rank Gaussian Variational Inference for Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1480
Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1481
Markovian Score Climbing: Variational Inference with KL(p||q)
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1482
Projected Stein Variational Gradient Descent
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1483
Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1484
SnapBoost: A Heterogeneous Boosting Machine
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1485
The Wasserstein Proximal Gradient Algorithm
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1486
Unbalanced Sobolev Descent
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1487
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1488
Multiparameter Persistence Image for Topological Machine Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1489
Learning with Differentiable Pertubed Optimizers
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1490
Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1491
Learning outside the Black-Box: The pursuit of interpretable models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1492
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1493
Random Reshuffling is Not Always Better
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1494
Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1495
Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1496
Online Sinkhorn: Optimal Transport distances from sample streams
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1497
A Non-Asymptotic Analysis for Stein Variational Gradient Descent
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1498
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1499
Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1500
The NetHack Learning Environment
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1501
Discovering Reinforcement Learning Algorithms
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1502
Latent World Models For Intrinsically Motivated Exploration
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1503
Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1504
Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1505
Learning to Incentivize Other Learning Agents
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1506
Calibration of Shared Equilibria in General Sum Partially Observable Markov Games
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1507
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1508
Learning to Play No-Press Diplomacy with Best Response Policy Iteration
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1509
A Boolean Task Algebra for Reinforcement Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1510
Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1511
Munchausen Reinforcement Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1512
Information-theoretic Task Selection for Meta-Reinforcement Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1513
Automatic Curriculum Learning through Value Disagreement
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1514
Combining Deep Reinforcement Learning and Search for Imperfect-Information Games
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1515
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1516
Learning to Prove Theorems by Learning to Generate Theorems
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1517
CHIP: A Hawkes Process Model for Continuous-time Networks with Scalable and Consistent Estimation
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1518
Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1519
Reasoning about Uncertainties in Discrete-Time Dynamical Systems using Polynomial Forms.
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1520
Taming Discrete Integration via the Boon of Dimensionality
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1521
Belief Propagation Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1522
Scalable Belief Propagation via Relaxed Scheduling
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1523
Probabilistic Circuits for Variational Inference in Discrete Graphical Models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1524
Towards Scalable Bayesian Learning of Causal DAGs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1525
A Novel Approach for Constrained Optimization in Graphical Models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1526
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1527
Factor Graph Grammars
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1528
Efficient Learning of Discrete Graphical Models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1529
Online Bayesian Goal Inference for Boundedly Rational Planning Agents
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1530
Greedy inference with structure-exploiting lazy maps
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1531
Biologically Inspired Mechanisms for Adversarial Robustness
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1532
Bayes Consistency vs. H-Consistency: The Interplay between Surrogate Loss Functions and the Scoring Function Class
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1533
Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1534
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1535
A Unified View of Label Shift Estimation
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1536
Calibrating Deep Neural Networks using Focal Loss
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1537
Distribution-free binary classification: prediction sets, confidence intervals and calibration
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1538
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1539
Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1540
Exchangeable Neural ODE for Set Modeling
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1541
Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1542
Further Analysis of Outlier Detection with Deep Generative Models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1543
Sample Complexity of Uniform Convergence for Multicalibration
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1544
Certifiably Adversarially Robust Detection of Out-of-Distribution Data
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1545
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1546
Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1547
Reducing Adversarially Robust Learning to Non-Robust PAC Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1548
Tensor Completion Made Practical
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1549
Online Matrix Completion with Side Information
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1550
Truncated Linear Regression in High Dimensions
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1551
Finer Metagenomic Reconstruction via Biodiversity Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1552
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1553
On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1554
Towards a Better Global Loss Landscape of GANs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1555
Implicit Regularization and Convergence for Weight Normalization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1556
Most ReLU Networks Suffer from $\ell^2$ Adversarial Perturbations
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1557
Geometric Exploration for Online Control
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1558
The Smoothed Possibility of Social Choice
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1559
Optimally Deceiving a Learning Leader in Stackelberg Games
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1561
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1562
Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1563
A Benchmark for Systematic Generalization in Grounded Language Understanding
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1564
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1565
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1566
Meta-Learning through Hebbian Plasticity in Random Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1567
Stable and expressive recurrent vision models
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1568
Identifying Learning Rules From Neural Network Observables
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1569
Deep active inference agents using Monte-Carlo methods
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1570
Learning Compositional Rules via Neural Program Synthesis
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1571
A Local Temporal Difference Code for Distributional Reinforcement Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1572
Inferring learning rules from animal decision-making
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1573
A Biologically Plausible Neural Network for Slow Feature Analysis
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1574
R-learning in actor-critic model offers a biologically relevant mechanism for sequential decision-making
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1575
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1576
Characterizing emergent representations in a space of candidate learning rules for deep networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1577
A simple normative network approximates local non-Hebbian learning in the cortex
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1578
A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1579
Detection as Regression: Certified Object Detection with Median Smoothing
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1580
Certifying Confidence via Randomized Smoothing
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1581
Reliable Graph Neural Networks via Robust Aggregation
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1582
PLLay: Efficient Topological Layer based on Persistent Landscapes
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1583
Network Diffusions via Neural Mean-Field Dynamics
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1584
Learning the Geometry of Wave-Based Imaging
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1585
Neuron Shapley: Discovering the Responsible Neurons
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1586
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1587
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1588
Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1589
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1590
Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1591
Discovering Symbolic Models from Deep Learning with Inductive Biases
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1592
Compositional Explanations of Neurons
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1593
Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1594
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1595
Telescoping Density-Ratio Estimation
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1596
On Testing of Samplers
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1597
Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1598
Deep Direct Likelihood Knockoffs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1599
Generalised Bayesian Filtering via Sequential Monte Carlo
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1600
Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1601
Bayesian Optimization of Risk Measures
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1602
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1603
Variance reduction for Random Coordinate Descent-Langevin Monte Carlo
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1604
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1605
Sequential Bayesian Experimental Design with Variable Cost Structure
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1606
Asymptotically Optimal Exact Minibatch Metropolis-Hastings
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1607
Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1608
Replica-Exchange Nos\'e-Hoover Dynamics for Bayesian Learning on Large Datasets
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1609
Stein Self-Repulsive Dynamics: Benefits From Past Samples
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1610
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1611
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1612
Bootstrapping neural processes
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1613
Sparse Learning with CART
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1614
Smooth And Consistent Probabilistic Regression Trees
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1615
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1616
Bayesian Deep Ensembles via the Neural Tangent Kernel
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1617
Predictive inference is free with the jackknife+-after-bootstrap
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1618
Hyperparameter Ensembles for Robustness and Uncertainty Quantification
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1619
Depth Uncertainty in Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1620
A Bayesian Perspective on Training Speed and Model Selection
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1621
Learning under Model Misspecification: Applications to Variational and Ensemble methods
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1622
Counterfactual Predictions under Runtime Confounding
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1623
Matérn Gaussian Processes on Riemannian Manifolds
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1624
Stationary Activations for Uncertainty Calibration in Deep Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1625
Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1626
On the Expressiveness of Approximate Inference in Bayesian Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1627
The Strong Screening Rule for SLOPE
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1628
Co-exposure Maximization in Online Social Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1629
Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1630
Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1631
MinMax Methods for Optimal Transport and Beyond: Regularization, Approximation and Numerics
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1632
Semialgebraic Optimization for Lipschitz Constants of ReLU Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1633
Parabolic Approximation Line Search for DNNs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1634
Batch normalization provably avoids ranks collapse for randomly initialised deep networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1635
Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1636
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1637
Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1638
A mean-field analysis of two-player zero-sum games
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1639
Robust Federated Learning: The Case of Affine Distribution Shifts
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1640
Learning compositional functions via multiplicative weight updates
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1641
Stochastic Optimization for Performative Prediction
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1642
Conformal Symplectic and Relativistic Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1643
On Power Laws in Deep Ensembles
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1644
Residual Distillation: Towards Portable Deep Neural Networks without Shortcuts
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1645
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1646
Self-Distillation as Instance-Specific Label Smoothing
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1647
On the training dynamics of deep networks with $L_2$ regularization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1648
Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1649
Batch Normalization Biases Residual Blocks Towards the Identity Function in Deep Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1650
Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1651
Bad Global Minima Exist and SGD Can Reach Them
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1652
The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1653
Ensemble Distillation for Robust Model Fusion in Federated Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1654
On Warm-Starting Neural Network Training
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1655
Predicting Training Time Without Training
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1656
Directional convergence and alignment in deep learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1657
Black-Box Ripper: Copying black-box models using generative evolutionary algorithms
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1658
Consistent feature selection for analytic deep neural networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1659
Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1660
Sampling from a k-DPP without looking at all items
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1661
Optimal Learning from Verified Training Data
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1662
Empirical Likelihood for Contextual Bandits
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1663
Sufficient dimension reduction for classification using principal optimal transport direction
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1664
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine Tuning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1665
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1666
Listening to Sounds of Silence for Speech Denoising
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1667
A Convolutional Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1668
Geometric All-way Boolean Tensor Decomposition
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1669
A novel variational form of the Schatten-$p$ quasi-norm
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1670
Distributionally Robust Parametric Maximum Likelihood Estimation
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1671
Adaptive Probing Policies for Shortest Path Routing
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1672
Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1673
Content Provider Dynamics and Coordination in Recommendation Ecosystems
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1674
Non-parametric Models for Non-negative Functions
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1675
Program Synthesis with Pragmatic Communication
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1676
Detecting Interactions from Neural Networks via Topological Analysis
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1677
Learning efficient task-dependent representations with synaptic plasticity
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1678
Modeling Shared responses in Neuroimaging Studies through MultiView ICA
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1679
Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1680
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1681
Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1682
Learning abstract structure for drawing by efficient motor program induction
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1683
Mutual exclusivity as a challenge for deep neural networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1684
Gibbs Sampling with People
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1685
Learning sparse codes from compressed representations with biologically plausible local wiring constraints
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1686
Shared Space Transfer Learning for analyzing multi-site fMRI data
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1687
Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1688
System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1689
An Unsupervised Information-Theoretic Perceptual Quality Metric
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1690
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1691
CoMIR: Contrastive Multimodal Image Representation for Registration
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1692
CrossTransformers: spatially-aware few-shot transfer
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1693
Contrastive learning of global and local features for medical image segmentation with limited annotations
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1694
3D Self-Supervised Methods for Medical Imaging
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1695
Unsupervised Learning of Dense Visual Representations
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1696
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1697
Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1698
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1699
LoCo: Local Contrastive Representation Learning
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1700
Self-Adaptively Learning to Demoiré from Focused and Defocused Image Pairs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1701
Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1702
Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1703
Differentiable Augmentation for Data-Efficient GAN Training
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1704
Comprehensive Attention Self-Distillation for Weakly-Supervised Object Detection
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1705
ContraGAN: Contrastive Learning for Conditional Image Generation
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1706
Inverting Gradients - How easy is it to break privacy in federated learning?
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1707
Principal Neighbourhood Aggregation for Graph Nets
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1708
Learning Graph Structure With A Finite-State Automaton Layer
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1709
Graph Cross Networks with Vertex Infomax Pooling
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1710
How hard is to distinguish graphs with graph neural networks?
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1711
Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1712
COPT: Coordinated Optimal Transport on Graphs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1713
Building powerful and equivariant graph neural networks with structural message-passing
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1714
Rethinking pooling in graph neural networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1715
Random Walk Graph Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1716
Path Integral Based Convolution and Pooling for Graph Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1717
Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1718
Towards Deeper Graph Neural Networks with Differentiable Group Normalization
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1719
Graphon Neural Networks and the Transferability of Graph Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1720
Convergence and Stability of Graph Convolutional Networks on Large Random Graphs
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1721
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1722
Parameterized Explainer for Graph Neural Network
[ Paper ]
Poster
Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1831
Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning
[ Paper ]
Affinity Workshop
Thu Dec 10 12:00 PM -- 02:10 PM (PST)
Indigenous in AI
Tutorial
Thu Dec 10 12:00 PM -- 12:50 PM (PST)
(Track1) Federated Learning and Analytics: Industry Meets Academia Q&A
Tutorial
Thu Dec 10 01:00 PM -- 01:50 PM (PST)
(Track3) Policy Optimization in Reinforcement Learning Q&A
Invited Talk
Thu Dec 10 05:00 PM -- 07:00 PM (PST)
The Genomic Bottleneck: A Lesson from Biology
Oral
Thu Dec 10 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Optimization
Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares Optimization
[ Paper ]
Oral
Thu Dec 10 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Health/AutoML/(Soft|Hard)ware
Theory-Inspired Path-Regularized Differential Network Architecture Search
[ Paper ]
Oral
Thu Dec 10 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Deep Learning
Is normalization indispensable for training deep neural network?
[ Paper ]
Oral
Thu Dec 10 06:00 PM -- 06:15 PM (PST) @ Orals & Spotlights: Neuroscience/Probabilistic
Point process models for sequence detection in high-dimensional neural spike trains
[ Paper ]
Oral
Thu Dec 10 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Optimization
The Primal-Dual method for Learning Augmented Algorithms
[ Paper ]
Oral
Thu Dec 10 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Health/AutoML/(Soft|Hard)ware
Improved Variational Bayesian Phylogenetic Inference with Normalizing Flows
[ Paper ]
Oral
Thu Dec 10 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Deep Learning
Understanding Approximate Fisher Information for Fast Convergence of Natural Gradient Descent in Wide Neural Networks
[ Paper ]
Oral
Thu Dec 10 06:15 PM -- 06:30 PM (PST) @ Orals & Spotlights: Neuroscience/Probabilistic
Reconstructing Perceptive Images from Brain Activity by Shape-Semantic GAN
[ Paper ]
Oral
Thu Dec 10 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Optimization
Fully Dynamic Algorithm for Constrained Submodular Optimization
[ Paper ]
Oral
Thu Dec 10 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Health/AutoML/(Soft|Hard)ware
Transferable Graph Optimizers for ML Compilers
[ Paper ]
Oral
Thu Dec 10 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Deep Learning
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks
[ Paper ]
Oral
Thu Dec 10 06:30 PM -- 06:45 PM (PST) @ Orals & Spotlights: Neuroscience/Probabilistic
A mathematical theory of cooperative communication
[ Paper ]
Break
Thu Dec 10 06:45 PM -- 07:00 PM (PST)
Break
Break
Thu Dec 10 06:45 PM -- 07:00 PM (PST)
Break
Spotlight
Thu Dec 10 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Optimization
Submodular Maximization Through Barrier Functions
[ Paper ]
Spotlight
Thu Dec 10 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Health/AutoML/(Soft|Hard)ware
A Study on Encodings for Neural Architecture Search
[ Paper ]
Spotlight
Thu Dec 10 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Deep Learning
Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamics
[ Paper ]
Spotlight
Thu Dec 10 07:00 PM -- 07:10 PM (PST) @ Orals & Spotlights: Neuroscience/Probabilistic
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds
[ Paper ]
Spotlight
Thu Dec 10 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Optimization
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method
[ Paper ]
Spotlight
Thu Dec 10 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Health/AutoML/(Soft|Hard)ware
Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding
[ Paper ]
Spotlight
Thu Dec 10 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Deep Learning
Kernel Based Progressive Distillation for Adder Neural Networks
[ Paper ]
Spotlight
Thu Dec 10 07:10 PM -- 07:20 PM (PST) @ Orals & Spotlights: Neuroscience/Probabilistic
Sinkhorn Natural Gradient for Generative Models
[ Paper ]
Spotlight
Thu Dec 10 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Optimization
A Single Recipe for Online Submodular Maximization with Adversarial or Stochastic Constraints
[ Paper ]
Spotlight
Thu Dec 10 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Health/AutoML/(Soft|Hard)ware
Evolving Normalization-Activation Layers
[ Paper ]
Spotlight
Thu Dec 10 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Deep Learning
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation
[ Paper ]
Spotlight
Thu Dec 10 07:20 PM -- 07:30 PM (PST) @ Orals & Spotlights: Neuroscience/Probabilistic
NVAE: A Deep Hierarchical Variational Autoencoder
[ Paper ]
Spotlight
Thu Dec 10 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Optimization
How many samples is a good initial point worth in Low-rank Matrix Recovery?
[ Paper ]
Spotlight
Thu Dec 10 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Health/AutoML/(Soft|Hard)ware
Open Graph Benchmark: Datasets for Machine Learning on Graphs
[ Paper ]
Spotlight
Thu Dec 10 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Deep Learning
Collegial Ensembles
[ Paper ]
Spotlight
Thu Dec 10 07:30 PM -- 07:40 PM (PST) @ Orals & Spotlights: Neuroscience/Probabilistic
Reciprocal Adversarial Learning via Characteristic Functions
[ Paper ]
Q&A
Thu Dec 10 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Thu Dec 10 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Thu Dec 10 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Thu Dec 10 07:40 PM -- 07:50 PM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Thu Dec 10 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Optimization
Projection Robust Wasserstein Distance and Riemannian Optimization
[ Paper ]
Spotlight
Thu Dec 10 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Health/AutoML/(Soft|Hard)ware
Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning
[ Paper ]
Spotlight
Thu Dec 10 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Deep Learning
Finite Versus Infinite Neural Networks: an Empirical Study
[ Paper ]
Spotlight
Thu Dec 10 07:50 PM -- 08:00 PM (PST) @ Orals & Spotlights: Neuroscience/Probabilistic
Incorporating Interpretable Output Constraints in Bayesian Neural Networks
[ Paper ]
Spotlight
Thu Dec 10 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Optimization
A Continuous-Time Mirror Descent Approach to Sparse Phase Retrieval
[ Paper ]
Spotlight
Thu Dec 10 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Health/AutoML/(Soft|Hard)ware
MCUNet: Tiny Deep Learning on IoT Devices
[ Paper ]
Spotlight
Thu Dec 10 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Deep Learning
Estimating Training Data Influence by Tracing Gradient Descent
[ Paper ]
Spotlight
Thu Dec 10 08:00 PM -- 08:10 PM (PST) @ Orals & Spotlights: Neuroscience/Probabilistic
Baxter Permutation Process
[ Paper ]
Spotlight
Thu Dec 10 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Optimization
SGD with shuffling: optimal rates without component convexity and large epoch requirements
[ Paper ]
Spotlight
Thu Dec 10 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Health/AutoML/(Soft|Hard)ware
Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming
[ Paper ]
Spotlight
Thu Dec 10 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Deep Learning
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients
[ Paper ]
Spotlight
Thu Dec 10 08:10 PM -- 08:20 PM (PST) @ Orals & Spotlights: Neuroscience/Probabilistic
Flexible mean field variational inference using mixtures of non-overlapping exponential families
[ Paper ]
Q&A
Thu Dec 10 08:20 PM -- 08:30 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Thu Dec 10 08:20 PM -- 08:30 PM (PST)
Joint Q&A for Preceeding Spotlights
Spotlight
Thu Dec 10 08:20 PM -- 08:30 PM (PST) @ Orals & Spotlights: Optimization
No-Regret Learning and Mixed Nash Equilibria: They Do Not Mix
[ Paper ]
Spotlight
Thu Dec 10 08:20 PM -- 08:30 PM (PST) @ Orals & Spotlights: Deep Learning
Part-dependent Label Noise: Towards Instance-dependent Label Noise
[ Paper ]
Break
Thu Dec 10 08:30 PM -- 09:00 PM (PST)
Break
Break
Thu Dec 10 08:30 PM -- 09:00 PM (PST)
Break
Q&A
Thu Dec 10 08:30 PM -- 08:40 PM (PST)
Joint Q&A for Preceeding Spotlights
Q&A
Thu Dec 10 08:30 PM -- 08:40 PM (PST)
Joint Q&A for Preceeding Spotlights
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1251
Linear-Sample Learning of Low-Rank Distributions
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1320
Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1724
Multi-label classification: do Hamming loss and subset accuracy really conflict with each other?
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1725
Generalization Bound of Gradient Descent for Non-Convex Metric Learning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1726
On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1727
Learning to Approximate a Bregman Divergence
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1728
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1729
Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1730
Learning to solve TV regularised problems with unrolled algorithms
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1731
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1732
Neural Networks Learning and Memorization with (almost) no Over-Parameterization
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1733
From Boltzmann Machines to Neural Networks and Back Again
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1734
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1735
Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1736
Projection Robust Wasserstein Distance and Riemannian Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1737
Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic View
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1738
Minimax Bounds for Generalized Linear Models
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1739
Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamics
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1740
Deep reconstruction of strange attractors from time series
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1741
STEER : Simple Temporal Regularization For Neural ODE
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1742
Learning Manifold Implicitly via Explicit Heat-Kernel Learning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1743
Better Set Representations For Relational Reasoning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1744
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1745
Model Inversion Networks for Model-Based Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1746
Variational Amodal Object Completion
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1747
Low Distortion Block-Resampling with Spatially Stochastic Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1748
Understanding Deep Architecture with Reasoning Layer
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1749
AdaTune: Adaptive Tensor Program Compilation Made Efficient
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1750
CircleGAN: Generative Adversarial Learning across Spherical Circles
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1751
SoftFlow: Probabilistic Framework for Normalizing Flow on Manifolds
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1752
Improved Techniques for Training Score-Based Generative Models
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1753
UDH: Universal Deep Hiding for Steganography, Watermarking, and Light Field Messaging
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1754
Deep Archimedean Copulas
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1755
Constraining Variational Inference with Geometric Jensen-Shannon Divergence
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1756
CO-Optimal Transport
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1757
OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1758
Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1759
Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1760
Improved Variational Bayesian Phylogenetic Inference with Normalizing Flows
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1761
HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1762
Noise-Contrastive Estimation for Multivariate Point Processes
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1763
Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier with Application to Real-Time Information Filtering on the Web
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1764
Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1765
Baxter Permutation Process
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1766
A mathematical theory of cooperative communication
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1767
All your loss are belong to Bayes
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1768
The Potts-Ising model for discrete multivariate data
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1769
Bidirectional Convolutional Poisson Gamma Dynamical Systems
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1770
Variational Bayesian Unlearning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1771
Theory-Inspired Path-Regularized Differential Network Architecture Search
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1772
Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1773
Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1774
AutoBSS: An Efficient Algorithm for Block Stacking Style Search
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1775
Semi-Supervised Neural Architecture Search
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1776
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1777
A Study on Encodings for Neural Architecture Search
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1778
Evolving Normalization-Activation Layers
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1779
Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1780
Auto Learning Attention
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1781
Transferable Graph Optimizers for ML Compilers
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1782
Adapting Neural Architectures Between Domains
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1783
Revisiting Parameter Sharing for Automatic Neural Channel Number Search
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1784
Neuron-level Structured Pruning using Polarization Regularizer
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1785
HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1786
MCUNet: Tiny Deep Learning on IoT Devices
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1788
Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1790
Bi-level Score Matching for Learning Energy-based Latent Variable Models
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1791
NVAE: A Deep Hierarchical Variational Autoencoder
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1792
Reciprocal Adversarial Learning via Characteristic Functions
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1793
Stochastic Stein Discrepancies
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1794
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1795
Incorporating Interpretable Output Constraints in Bayesian Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1796
Quantile Propagation for Wasserstein-Approximate Gaussian Processes
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1797
Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous Variables
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1798
Walsh-Hadamard Variational Inference for Bayesian Deep Learning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1799
f-Divergence Variational Inference
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1800
Flexible mean field variational inference using mixtures of non-overlapping exponential families
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1801
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1802
Improving Online Rent-or-Buy Algorithms with Sequential Decision Making and ML Predictions
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1803
Community detection using fast low-cardinality semidefinite programming
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1804
Online Optimization with Memory and Competitive Control
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1805
Simple and Fast Algorithm for Binary Integer and Online Linear Programming
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1806
A Single Recipe for Online Submodular Maximization with Adversarial or Stochastic Constraints
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1807
Online Convex Optimization Over Erdos-Renyi Random Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1808
Thunder: a Fast Coordinate Selection Solver for Sparse Learning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1809
Deterministic Approximation for Submodular Maximization over a Matroid in Nearly Linear Time
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1810
The Primal-Dual method for Learning Augmented Algorithms
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1812
Fully Dynamic Algorithm for Constrained Submodular Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1813
Submodular Maximization Through Barrier Functions
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1814
Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1815
Robust Sequence Submodular Maximization
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1816
Continuous Submodular Maximization: Beyond DR-Submodularity
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1817
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1818
Towards More Practical Adversarial Attacks on Graph Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1819
Boundary thickness and robustness in learning models
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1820
Exploiting weakly supervised visual patterns to learn from partial annotations
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1821
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1822
Part-dependent Label Noise: Towards Instance-dependent Label Noise
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1823
Digraph Inception Convolutional Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1824
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1825
Self-Adaptive Training: beyond Empirical Risk Minimization
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1826
Debugging Tests for Model Explanations
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1827
Point process models for sequence detection in high-dimensional neural spike trains
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1828
Lamina-specific neuronal properties promote robust, stable signal propagation in feedforward networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1829
Reconstructing Perceptive Images from Brain Activity by Shape-Semantic GAN
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1830
High-contrast “gaudy” images improve the training of deep neural network models of visual cortex
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1832
Weakly-Supervised Reinforcement Learning for Controllable Behavior
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1833
Predictive Information Accelerates Learning in RL
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1834
The route to chaos in routing games: When is price of anarchy too optimistic?
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1835
Graph Meta Learning via Local Subgraphs
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1836
Graph Information Bottleneck
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1837
Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1838
Tree! I am no Tree! I am a low dimensional Hyperbolic Embedding
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1839
Scalable Graph Neural Networks via Bidirectional Propagation
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1840
Neural Message Passing for Multi-Relational Ordered and Recursive Hypergraphs
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1841
A graph similarity for deep learning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1842
Implicit Graph Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1843
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1844
Disentangling Human Error from Ground Truth in Segmentation of Medical Images
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1845
Graph Policy Network for Transferable Active Learning on Graphs
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1846
Open Graph Benchmark: Datasets for Machine Learning on Graphs
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1847
Factorizable Graph Convolutional Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1848
Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network Learning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1849
Natural Graph Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1850
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1851
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1852
Sinkhorn Natural Gradient for Generative Models
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1853
Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1854
How many samples is a good initial point worth in Low-rank Matrix Recovery?
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1855
Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1856
Faster Randomized Infeasible Interior Point Methods for Tall/Wide Linear Programs
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1857
Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1858
Tight last-iterate convergence rates for no-regret learning in multi-player games
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1859
A General Large Neighborhood Search Framework for Solving Integer Linear Programs
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1860
Sinkhorn Barycenter via Functional Gradient Descent
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1861
Improved Analysis of Clipping Algorithms for Non-convex Optimization
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1862
A Continuous-Time Mirror Descent Approach to Sparse Phase Retrieval
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1863
Federated Accelerated Stochastic Gradient Descent
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1864
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1865
SGD with shuffling: optimal rates without component convexity and large epoch requirements
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1866
No-Regret Learning and Mixed Nash Equilibria: They Do Not Mix
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1867
Generalized Leverage Score Sampling for Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1868
Passport-aware Normalization for Deep Model Protection
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1869
Model Rubik’s Cube: Twisting Resolution, Depth and Width for TinyNets
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1870
Neural Networks Fail to Learn Periodic Functions and How to Fix It
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1871
Finite Versus Infinite Neural Networks: an Empirical Study
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1872
Understanding Approximate Fisher Information for Fast Convergence of Natural Gradient Descent in Wide Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1874
Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1875
Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1876
Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep Learning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1877
A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1878
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1879
Coresets for Robust Training of Deep Neural Networks against Noisy Labels
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1880
Learning Deep Attribution Priors Based On Prior Knowledge
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1881
Estimating Training Data Influence by Tracing Gradient Descent
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1882
Escaping Saddle-Point Faster under Interpolation-like Conditions
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1883
Learning Loss for Test-Time Augmentation
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1884
Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1885
MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1886
The Dilemma of TriHard Loss and an Element-Weighted TriHard Loss for Person Re-Identification
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1887
Is normalization indispensable for training deep neural network?
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1888
SCOP: Scientific Control for Reliable Neural Network Pruning
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1889
Train-by-Reconnect: Decoupling Locations of Weights from Their Values
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1890
Deep Metric Learning with Spherical Embedding
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1891
Kernel Based Progressive Distillation for Adder Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1892
Top-KAST: Top-K Always Sparse Training
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1893
Task-Oriented Feature Distillation
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1894
Rotated Binary Neural Network
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1895
Agree to Disagree: Adaptive Ensemble Knowledge Distillation in Gradient Space
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1896
Sparse Weight Activation Training
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1897
Recurrent Quantum Neural Networks
[ Paper ]
Poster
Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1898
Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee
[ Paper ]
Workshop
Thu Dec 10 11:00 PM -- 12:00 PM (PST)
Topological Data Analysis and Beyond
Workshop
Fri Dec 11 01:20 AM -- 01:25 PM (PST)
Privacy Preserving Machine Learning - PriML and PPML Joint Edition
Workshop
Fri Dec 11 03:15 AM -- 04:30 PM (PST)
OPT2020: Optimization for Machine Learning
Workshop
Fri Dec 11 05:30 AM -- 02:10 PM (PST)
Advances and Opportunities: Machine Learning for Education
Workshop
Fri Dec 11 05:45 AM -- 02:00 PM (PST)
Differential Geometry meets Deep Learning (DiffGeo4DL)
Workshop
Fri Dec 11 06:00 AM -- 04:20 PM (PST)
Machine Learning for Health (ML4H): Advancing Healthcare for All
Workshop
Fri Dec 11 06:00 AM -- 11:00 AM (PST)
Workshop on Dataset Curation and Security
Workshop
Fri Dec 11 06:00 AM -- 05:50 PM (PST)
First Workshop on Quantum Tensor Networks in Machine Learning
Workshop
Fri Dec 11 06:00 AM -- 06:15 PM (PST)
Learning Meaningful Representations of Life (LMRL.org)
Workshop
Fri Dec 11 06:15 AM -- 02:30 PM (PST)
The pre-registration experiment: an alternative publication model for machine learning research
Workshop
Fri Dec 11 06:45 AM -- 02:30 PM (PST)
Differentiable computer vision, graphics, and physics in machine learning
Workshop
Fri Dec 11 06:50 AM -- 04:25 PM (PST)
Self-Supervised Learning for Speech and Audio Processing
Workshop
Fri Dec 11 06:50 AM -- 04:50 PM (PST)
Causal Discovery and Causality-Inspired Machine Learning
Workshop
Fri Dec 11 07:00 AM -- 12:30 PM (PST)
ML Competitions at the Grassroots (CiML 2020)
Workshop
Fri Dec 11 07:00 AM -- 03:15 PM (PST)
Machine Learning and the Physical Sciences
Workshop
Fri Dec 11 07:30 AM -- 04:00 PM (PST)
Workshop on Deep Learning and Inverse Problems
Workshop
Fri Dec 11 07:55 AM -- 05:00 PM (PST)
Machine Learning for Autonomous Driving
Workshop
Fri Dec 11 08:00 AM -- 04:00 PM (PST)
Crowd Science Workshop: Remoteness, Fairness, and Mechanisms as Challenges of Data Supply by Humans for Automation
Workshop
Fri Dec 11 08:00 AM -- 07:15 PM (PST)
Object Representations for Learning and Reasoning
Workshop
Fri Dec 11 08:30 AM -- 09:00 PM (PST)
ML Retrospectives, Surveys & Meta-Analyses (ML-RSA)
Workshop
Fri Dec 11 08:40 AM -- 05:25 PM (PST)
KR2ML - Knowledge Representation and Reasoning Meets Machine Learning
Workshop
Fri Dec 11 08:40 AM -- 05:30 PM (PST)
BabyMind: How Babies Learn and How Machines Can Imitate
Workshop
Fri Dec 11 09:00 AM -- 04:00 PM (PST)
Machine Learning for Economic Policy
Workshop
Sat Dec 12 01:00 AM -- 12:10 PM (PST)
Algorithmic Fairness through the Lens of Causality and Interpretability
Workshop
Sat Dec 12 03:00 AM -- 04:00 PM (PST)
Learning Meets Combinatorial Algorithms
Workshop
Sat Dec 12 04:00 AM -- 02:00 PM (PST)
Machine Learning for the Developing World (ML4D): Improving Resilience
Workshop
Sat Dec 12 04:30 AM -- 03:45 PM (PST)
Biological and Artificial Reinforcement Learning
Workshop
Sat Dec 12 04:45 AM -- 02:45 PM (PST)
I Can’t Believe It’s Not Better! Bridging the gap between theory and empiricism in probabilistic machine learning
Workshop
Sat Dec 12 04:50 AM -- 03:00 PM (PST)
Machine Learning for Engineering Modeling, Simulation and Design
Workshop
Sat Dec 12 05:15 AM -- 03:00 PM (PST)
Machine Learning for Creativity and Design 4.0
Workshop
Sat Dec 12 05:30 AM -- 03:00 PM (PST)
Navigating the Broader Impacts of AI Research
Workshop
Sat Dec 12 06:00 AM -- 02:00 PM (PST)
MLPH: Machine Learning in Public Health
Workshop
Sat Dec 12 06:00 AM -- 04:30 PM (PST)
Beyond BackPropagation: Novel Ideas for Training Neural Architectures
Workshop
Sat Dec 12 06:30 AM -- 02:30 PM (PST)
Interpretable Inductive Biases and Physically Structured Learning
Workshop
Sat Dec 12 07:00 AM -- 02:10 PM (PST)
Talking to Strangers: Zero-Shot Emergent Communication
Workshop
Sat Dec 12 07:50 AM -- 05:10 PM (PST)
Shared Visual Representations in Human and Machine Intelligence (SVRHM)
Workshop
Sat Dec 12 08:00 AM -- 06:00 PM (PST)
Machine Learning for Structural Biology
Workshop
Sat Dec 12 08:00 AM -- 06:00 PM (PST)
Second Workshop on AI for Humanitarian Assistance and Disaster Response
Workshop
Sat Dec 12 08:00 AM -- 03:50 PM (PST)
Consequential Decisions in Dynamic Environments
Workshop
Sat Dec 12 08:15 AM -- 08:00 PM (PST)
HAMLETS: Human And Model in the Loop Evaluation and Training Strategies
Workshop
Sat Dec 12 08:20 AM -- 07:10 PM (PST)
International Workshop on Scalability, Privacy, and Security in Federated Learning (SpicyFL 2020)
Workshop
Sat Dec 12 08:30 AM -- 07:30 PM (PST)
The Challenges of Real World Reinforcement Learning
Workshop
Sat Dec 12 08:30 AM -- 04:10 PM (PST)
Workshop on Computer Assisted Programming (CAP)
Workshop
Sat Dec 12 08:50 AM -- 06:40 PM (PST)
Self-Supervised Learning -- Theory and Practice
Workshop
Sat Dec 12 09:20 AM -- 06:30 PM (PST)
Deep Learning through Information Geometry