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Dec. 2, 2018 Expo schedule » New in ML »

Timezone: America/Montreal »

Indicates the beginning of a session

 Tue Dec 04, 2018

Time Room 210 Room 517 AB
05:00 PM (Posters)
Point process latent variable models of larval zebrafish behavior Room 210 #1
Provably Correct Automatic Sub-Differentiation for Qualified Programs Room 210 #2
Neural Ordinary Differential Equations Room 210 #3
Information Constraints on Auto-Encoding Variational Bayes Room 210 #4
Robustness of conditional GANs to noisy labels Room 210 #5
Bias and Generalization in Deep Generative Models: An Empirical Study Room 210 #6
Probabilistic Neural Programmed Networks for Scene Generation Room 210 #7
Step Size Matters in Deep Learning Room 210 #8
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Room 210 #9
How Does Batch Normalization Help Optimization? Room 210 #10
Towards Robust Detection of Adversarial Examples Room 210 #11
Training Neural Networks Using Features Replay Room 210 #12
Faster Neural Networks Straight from JPEG Room 210 #13
Hierarchical Graph Representation Learning with Differentiable Pooling Room 210 #14
Bayesian Model-Agnostic Meta-Learning Room 210 #15
Evolved Policy Gradients Room 210 #16
BourGAN: Generative Networks with Metric Embeddings Room 210 #17
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation Room 210 #18
Generalisation of structural knowledge in the hippocampal-entorhinal system Room 210 #19
Task-Driven Convolutional Recurrent Models of the Visual System Room 210 #20
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding Room 210 #21
Extracting Relationships by Multi-Domain Matching Room 210 #22
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding Room 210 #23
Beauty-in-averageness and its contextual modulations: A Bayesian statistical account Room 210 #24
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video Room 210 #25
A probabilistic population code based on neural samples Room 210 #26
cpSGD: Communication-efficient and differentially-private distributed SGD Room 210 #27
Bounded-Loss Private Prediction Markets Room 210 #28
Ex ante coordination and collusion in zero-sum multi-player extensive-form games Room 210 #29
Model-Agnostic Private Learning Room 210 #30
Adversarially Robust Generalization Requires More Data Room 210 #31
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC Room 210 #32
A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices Room 210 #33
Designing by Training: Acceleration Neural Network for Fast High-Dimensional Convolution Room 210 #34
Greedy Hash: Towards Fast Optimization for Accurate Hash Coding in CNN Room 210 #35
Generative Probabilistic Novelty Detection with Adversarial Autoencoders Room 210 #36
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution Room 210 #37
Compact Generalized Non-local Network Room 210 #38
BinGAN: Learning Compact Binary Descriptors with a Regularized GAN Room 210 #39
RenderNet: A deep convolutional network for differentiable rendering from 3D shapes Room 210 #40
LF-Net: Learning Local Features from Images Room 210 #41
Unsupervised Learning of Shape and Pose with Differentiable Point Clouds Room 210 #42
Modelling and unsupervised learning of symmetric deformable object categories Room 210 #43
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation Room 210 #44
Image Inpainting via Generative Multi-column Convolutional Neural Networks Room 210 #45
Beyond Grids: Learning Graph Representations for Visual Recognition Room 210 #46
Foreground Clustering for Joint Segmentation and Localization in Videos and Images Room 210 #47
LinkNet: Relational Embedding for Scene Graph Room 210 #48
Context-aware Synthesis and Placement of Object Instances Room 210
Geometry-Aware Recurrent Neural Networks for Active Visual Recognition Room 210 #50
See and Think: Disentangling Semantic Scene Completion Room 210 #51
Active Matting Room 210 #52
A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation Room 210 #53
Turbo Learning for CaptionBot and DrawingBot Room 210 #54
Dialog-based Interactive Image Retrieval Room 210 #55
Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation Room 210 #56
Sequential Context Encoding for Duplicate Removal Room 210 #57
Hybrid Knowledge Routed Modules for Large-scale Object Detection Room 210 #58
SNIPER: Efficient Multi-Scale Training Room 210 #59
Revisiting Multi-Task Learning with ROCK: a Deep Residual Auxiliary Block for Visual Detection Room 210 #60
MetaAnchor: Learning to Detect Objects with Customized Anchors Room 210 #61
Learning Hierarchical Semantic Image Manipulation through Structured Representations Room 210 #62
Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation Room 210 #63
3D-Aware Scene Manipulation via Inverse Graphics Room 210 #64
FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification Room 210 #65
Sequence-to-Segment Networks for Segment Detection Room 210 #66
Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning Room 210 #67
DeepExposure: Learning to Expose Photos with Asynchronously Reinforced Adversarial Learning Room 210 #68
Self-Erasing Network for Integral Object Attention Room 210 #69
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction Room 210 #70
DifNet: Semantic Segmentation by Diffusion Networks Room 210 #71
Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization Room 210 #72
Attention in Convolutional LSTM for Gesture Recognition Room 210 #73
Partially-Supervised Image Captioning Room 210 #74
Learning to Specialize with Knowledge Distillation for Visual Question Answering Room 210 #75
Chain of Reasoning for Visual Question Answering Room 210 #76
Learning Conditioned Graph Structures for Interpretable Visual Question Answering Room 210 #77
Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering Room 210 #78
Overcoming Language Priors in Visual Question Answering with Adversarial Regularization Room 210 #79
Non-Local Recurrent Network for Image Restoration Room 210 #80
Neural Nearest Neighbors Networks Room 210 #81
Training deep learning based denoisers without ground truth data Room 210 #82
Adversarial Regularizers in Inverse Problems Room 210 #83
Densely Connected Attention Propagation for Reading Comprehension Room 210 #84
Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation Room 210 #85
e-SNLI: Natural Language Inference with Natural Language Explanations Room 210 #86
The challenge of realistic music generation: modelling raw audio at scale Room 210 #87
Fully Neural Network Based Speech Recognition on Mobile and Embedded Devices Room 210 #88
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis Room 210 #89
SING: Symbol-to-Instrument Neural Generator Room 210 #90
Neural Voice Cloning with a Few Samples Room 210 #91
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking Room 210 #92
Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base Room 210 #93
Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization Room 210 #94
Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog Room 210 #95
Trajectory Convolution for Action Recognition Room 210 #96
Video Prediction via Selective Sampling Room 210 #97
Unsupervised Learning of Artistic Styles with Archetypal Style Analysis Room 210 #98
Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples Room 210 #99
Speaker-Follower Models for Vision-and-Language Navigation Room 210 #100
Neural Code Comprehension: A Learnable Representation of Code Semantics Room 517 AB #101
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare Room 517 AB #102
Distilled Wasserstein Learning for Word Embedding and Topic Modeling Room 517 AB #103
Learning to Optimize Tensor Programs Room 517 AB #104
Learning to Solve SMT Formulas Room 517 AB #105
Data center cooling using model-predictive control Room 517 AB #106
Bayesian Inference of Temporal Task Specifications from Demonstrations Room 517 AB #107
Training Deep Neural Networks with 8-bit Floating Point Numbers Room 517 AB #108
Snap ML: A Hierarchical Framework for Machine Learning Room 517 AB #109
Learning filter widths of spectral decompositions with wavelets Room 517 AB #110
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks Room 517 AB #111
Latent Gaussian Activity Propagation: Using Smoothness and Structure to Separate and Localize Sounds in Large Noisy Environments Room 517 AB #112
Inferring Latent Velocities from Weather Radar Data using Gaussian Processes Room 517 AB #113
Bayesian Nonparametric Spectral Estimation Room 517 AB #114
Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders Room 517 AB #115
Precision and Recall for Time Series Room 517 AB #116
Deep Generative Markov State Models Room 517 AB #117
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with $\beta$-Divergences Room 517 AB #118
Regularization Learning Networks: Deep Learning for Tabular Datasets Room 517 AB #119
Generative modeling for protein structures Room 517 AB #120
Geometry Based Data Generation Room 517 AB #121
Learning Concave Conditional Likelihood Models for Improved Analysis of Tandem Mass Spectra Room 517 AB #122
Generalizing Tree Probability Estimation via Bayesian Networks Room 517 AB #123
Learning Temporal Point Processes via Reinforcement Learning Room 517 AB #124
Exponentially Weighted Imitation Learning for Batched Historical Data Room 517 AB #125
Evidential Deep Learning to Quantify Classification Uncertainty Room 517 AB #126
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Room 517 AB #127
Towards Robust Interpretability with Self-Explaining Neural Networks Room 517 AB #128
Model Agnostic Supervised Local Explanations Room 517 AB #129
To Trust Or Not To Trust A Classifier Room 517 AB #130
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer Room 517 AB #131
Hunting for Discriminatory Proxies in Linear Regression Models Room 517 AB #132
Empirical Risk Minimization Under Fairness Constraints Room 517 AB #133
Approximation algorithms for stochastic clustering Room 517 AB #134
Re-evaluating evaluation Room 517 AB #135
Does mitigating ML's impact disparity require treatment disparity? Room 517 AB #136
Enhancing the Accuracy and Fairness of Human Decision Making Room 517 AB #137
The Price of Fair PCA: One Extra dimension Room 517 AB #138
Practical Methods for Graph Two-Sample Testing Room 517 AB #139
Topkapi: Parallel and Fast Sketches for Finding Top-K Frequent Elements Room 517 AB #140
KDGAN: Knowledge Distillation with Generative Adversarial Networks Room 517 AB #141
Modeling Dynamic Missingness of Implicit Feedback for Recommendation Room 517 AB #142
Gamma-Poisson Dynamic Matrix Factorization Embedded with Metadata Influence Room 517 AB #143
Non-metric Similarity Graphs for Maximum Inner Product Search Room 517 AB #144
Norm-Ranging LSH for Maximum Inner Product Search Room 517 AB #145
A Dual Framework for Low-rank Tensor Completion Room 517 AB #146
Low-Rank Tucker Decomposition of Large Tensors Using TensorSketch Room 517 AB #147
Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization Room 517 AB #148
Semidefinite relaxations for certifying robustness to adversarial examples Room 517 AB #149
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences Room 517 AB #150
Differentially Private Testing of Identity and Closeness of Discrete Distributions Room 517 AB #151
Differentially Private k-Means with Constant Multiplicative Error Room 517 AB #152
Local Differential Privacy for Evolving Data Room 517 AB #153
Adversarial Attacks on Stochastic Bandits Room 517 AB #154
Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization Room 517 AB #155
A Spectral View of Adversarially Robust Features Room 517 AB #156
Efficient Formal Safety Analysis of Neural Networks Room 517 AB #157
Contamination Attacks and Mitigation in Multi-Party Machine Learning Room 517 AB #158
Explaining Deep Learning Models -- A Bayesian Non-parametric Approach Room 517 AB #159
Data-Driven Clustering via Parameterized Lloyd's Families Room 517 AB #160
Manifold Structured Prediction Room 517 AB #161
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs Room 517 AB #162
Masking: A New Perspective of Noisy Supervision Room 517 AB #163
Supervising Unsupervised Learning Room 517 AB #164
One-Shot Unsupervised Cross Domain Translation Room 517 AB #165
Neural Architecture Search with Bayesian Optimisation and Optimal Transport Room 517 AB #166
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning Room 517 AB #167
Completing State Representations using Spectral Learning Room 517 AB #168
Data-Efficient Hierarchical Reinforcement Learning Room 517 AB #169
The Cluster Description Problem - Complexity Results, Formulations and Approximations Room 517 AB #170