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Poster
Dates n/a. @ None
Integration Methods and Optimization Algorithms
Damien Scieur · Vincent Roulet · Francis Bach · Alexandre d'Aspremont
Poster
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Variational Inference for Gaussian Process Models with Linear Complexity
Poster
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Saliency-based Sequential Image Attention with Multiset Prediction
Poster
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Real-Time Bidding with Side Information
Poster
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Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models
Poster
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A-NICE-MC: Adversarial Training for MCMC
Poster
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Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes
Poster
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Learning Graph Embeddings with Embedding Propagation
Poster
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Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization
Poster
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PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Poster
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GibbsNet: Iterative Adversarial Inference for Deep Graphical Models
Poster
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Perturbative Black Box Variational Inference
Poster
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Teaching Machines to Describe Images with Natural Language Feedback
Poster
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Stochastic and Adversarial Online Learning without Hyperparameters
Poster
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Riemannian approach to batch normalization
Poster
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Hindsight Experience Replay
Poster
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Polynomial time algorithms for dual volume sampling
Poster
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Fair Clustering Through Fairlets
Poster
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Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling
Poster
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Active Exploration for Learning Symbolic Representations
Poster
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Position-based Multiple-play Multi-armed Bandit Problem with Unknown Position Bias
Poster
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Online Reinforcement Learning in Stochastic Games
Poster
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Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes
Poster
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A simple neural network module for relational reasoning
Poster
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DropoutNet: Addressing Cold Start in Recommender Systems
Poster
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Maximum Margin Interval Trees
Poster
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Online Learning for Multivariate Hawkes Processes
Poster
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Hash Embeddings for Efficient Word Representations
Poster
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Fast, Sample-Efficient Algorithms for Structured Phase Retrieval
Poster
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Group Additive Structure Identification for Kernel Nonparametric Regression
Poster
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Monte-Carlo Tree Search by Best Arm Identification
Poster
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Minimax Estimation of Bandable Precision Matrices
Poster
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Selective Classification for Deep Neural Networks
Poster
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Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds
Poster
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Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon
Poster
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Multi-Task Learning for Contextual Bandits
Poster
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Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto Simplex
Poster
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Context Selection for Embedding Models
Poster
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Scalable Variational Inference for Dynamical Systems
Poster
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Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions
Poster
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Investigating the learning dynamics of deep neural networks using random matrix theory
Poster
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Stochastic Approximation for Canonical Correlation Analysis
Poster
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A unified approach to interpreting model predictions
Poster
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Beyond Worst-case: A Probabilistic Analysis of Affine Policies in Dynamic Optimization
Poster
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Adaptive Classification for Prediction Under a Budget
Poster
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Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation
Poster
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Robust Optimization for Non-Convex Objectives
Poster
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QMDP-Net: Deep Learning for Planning under Partial Observability
Poster
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Affine-Invariant Online Optimization
Poster
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Query Complexity of Clustering with Side Information
Poster
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SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud
Poster
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Balancing information exposure in social networks
Poster
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Overcoming Catastrophic Forgetting by Incremental Moment Matching
Poster
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Non-Stationary Spectral Kernels
Poster
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Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs
Poster
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Targeting EEG/LFP Synchrony with Neural Nets
Poster
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Scalable Model Selection for Belief Networks
Poster
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Ranking Data with Continuous Labels through Oriented Recursive Partitions
Poster
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Doubly Stochastic Variational Inference for Deep Gaussian Processes
Poster
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Discovering Potential Influence via Information Bottleneck
Poster
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Convergence rates of a partition based Bayesian multivariate density estimation method
Poster
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Simple strategies for recovering inner products from coarsely quantized random projections
Poster
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Streaming Robust Submodular Maximization:A Partitioned Thresholding Approach
Poster
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Reconstruct & Crush Network
Poster
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Training recurrent networks to generate hypotheses about how the brain solves hard navigation problems
Poster
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Trimmed Density Ratio Estimation
Poster
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Online Learning of Optimal Bidding Strategy in Repeated Multi-Commodity Auctions
Poster
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DisTraL: Robust multitask reinforcement learning
Poster
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Visual Interaction Networks
Poster
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A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks
Poster
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Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers
Poster
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Dual Path Networks
Poster
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Improved Graph Laplacian via Geometric Self-Consistency
Poster
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The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities
Poster
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Is Input Sparsity Time Possible for Kernel Low-Rank Approximation?
Poster
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Federated Multi-Task Learning
Poster
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Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix Multiplication
Poster
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Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net
Poster
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Safe Adaptive Importance Sampling
Poster
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A Decomposition of Forecast Error in Prediction Markets
Poster
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Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach
Poster
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A Minimax Optimal Algorithm for Crowdsourcing
Poster
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Tensor encoding and decomposition of brain connectomes with application to tractography evaluation
Poster
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Adversarial Symmetric Variational Autoencoder
Poster
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Policy Gradient With Value Function Approximation For Collective Multiagent Planning
Poster
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K-Medoids For K-Means Seeding
Poster
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Identifying Outlier Arms in Multi-Armed Bandit
Poster
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Online Learning with Transductive Regret
Poster
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Self-supervised Learning of Motion Capture
Poster
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Triangle Generative Adversarial Networks
Poster
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Preserving Proximity and Global Ranking for Node Embedding
Poster
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Bayesian Optimization with Gradients
Poster
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Second-order Optimization in Deep Reinforcement Learning using Kronecker-factored Approximation
Poster
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Renyi Differential Privacy Mechanisms for Posterior Sampling
Poster
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Online Learning with a Hint
Poster
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Identification of Gaussian Process State Space Models
Poster
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Robust Imitation of Diverse Behaviors
Poster
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Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent
Poster
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SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks
Poster
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Local Aggregative Games
Poster
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A Sample Complexity Measure with Applications to Learning Optimal Auctions
Poster
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Thinking Fast and Slow with Deep Learning and Tree Search
Poster
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EEG-GRAPH: A Factor Graph Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms
Poster
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Improving the Expected Improvement Algorithm
Poster
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Hybrid Reward Architecture for Reinforcement Learning
Poster
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Approximate Supermodularity Bounds for Experimental Design
Poster
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A Greedy Approach for Budgeted Maximum Inner Product Search
Poster
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Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification
Poster
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AdaGAN: Boosting Generative Models
Poster
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Straggler Mitigation in Distributed Optimization Through Data Encoding
Poster
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Multi-View Decision Processes
Poster
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Plan, Attend, Generate: Planning for Sequence-to-Sequence Models
Poster
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Task-based End-to-end Model Learning in Stochastic Optimization
Poster
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Towards Understanding Adversarial Learning for Joint Distribution Matching
Poster
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Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting
Poster
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On the Complexity of Learning Neural Networks
Poster
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Hierarchical Implicit Models and Likelihood-Free Variational Inference
Poster
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Improved Semi-supervised Learning with GANs using Manifold Invariances
Poster
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Approximation and Convergence Properties of Generative Adversarial Learning
Poster
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From Bayesian Sparsity to Gated Recurrent Nets
Poster
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Min-Max Propagation
Poster
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What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
Poster
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On Fairness and Calibration
Poster
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Gradient descent GAN optimization is locally stable
Poster
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Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks
Poster
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Dualing GANs
Poster
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Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
Poster
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Do Deep Neural Networks Suffer from Crowding?
Poster
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Learning from Complementary Labels
Poster
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More powerful and flexible rules for online FDR control with memory and weights
Poster
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Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes
Poster
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Discriminative State Space Models
Poster
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Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations
Poster
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Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
Poster
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Gradients of Generative Models for Improved Discriminative Analysis of Tandem Mass Spectra
Poster
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Asynchronous Parallel Coordinate Minimization for MAP Inference
Poster
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Multiscale Quantization for Fast Similarity Search
Poster
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Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space
Poster
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Improved Training of Wasserstein GANs
Poster
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Optimally Learning Populations of Parameters
Poster
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Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods
Poster
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Training Quantized Nets: A Deeper Understanding
Poster
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Permutation-based Causal Inference Algorithms with Interventions
Poster
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Time-dependent spatially varying graphical models, with application to brain fMRI data analysis
Poster
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Gradient Methods for Submodular Maximization
Poster
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Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization
Poster
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Maximizing the Spread of Influence from Training Data
Poster
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Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaos
Poster
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Learning Neural Representations of Human Cognition across Many fMRI Studies
Poster
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A KL-LUCB algorithm for Large-Scale Crowdsourcing
Poster
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Collaborative Deep Learning in Fixed Topology Networks
Poster
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Fast-Slow Recurrent Neural Networks
Poster
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Learning Disentangled Representations with Semi-Supervised Deep Generative Models
Poster
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Learning to Generalize Intrinsic Images with a Structured Disentangling Autoencoder
Poster
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A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control
Poster
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Fader Networks: Generating Image Variations by Sliding Attribute Values
Poster
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Action Centered Contextual Bandits
Poster
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Estimating Mutual Information for Discrete-Continuous Mixtures
Poster
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Attention is All you Need
Poster
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Recurrent Ladder Networks
Poster
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Parameter-Free Online Learning via Model Selection
Poster
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Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction
Poster
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Unbounded cache model for online language modeling with open vocabulary
Poster
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Predictive State Recurrent Neural Networks
Poster
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Early stopping for kernel boosting algorithms: A general analysis with localized complexities
Poster
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SVCCA: Singular Vector Canonical Correlation Analysis for Deep Understanding and Improvement
Poster
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Convolutional Phase Retrieval
Poster
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Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma
Poster
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Gaussian Quadrature for Kernel Features
Poster
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Value Prediction Network
Poster
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On Learning Errors of Structured Prediction with Approximate Inference
Poster
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Efficient Second-Order Online Kernel Learning with Adaptive Embedding
Poster
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Implicit Regularization in Matrix Factorization
Poster
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Optimal Shrinkage of Singular Values Under Random Data Contamination
Poster
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Delayed Mirror Descent in Continuous Games
Poster
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Asynchronous Coordinate Descent under More Realistic Assumptions
Poster
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Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls
Poster
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Hierarchical Clustering Beyond the Worst-Case
Poster
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Invariance and Stability of Deep Convolutional Representations
Poster
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Statistical Cost Sharing
Poster
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The Expressive Power of Neural Networks: A View from the Width
Poster
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Spectrally-normalized margin bounds for neural networks
Poster
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Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes
Poster
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Population Matching Discrepancy and Applications in Deep Learning
Poster
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Scalable Planning with Tensorflow for Hybrid Nonlinear Domains
Poster
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Boltzmann Exploration Done Right
Poster
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Towards the ImageNet-CNN of NLP: Pretraining Sentence Encoders with Machine Translation
Poster
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Neural Discrete Representation Learning
Poster
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Generalizing GANs: A Turing Perspective
Poster
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Scalable Log Determinants for Gaussian Process Kernel Learning
Poster
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Poincaré Embeddings for Learning Hierarchical Representations
Poster
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Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
Poster
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Learning Combinatorial Optimization Algorithms over Graphs
Poster
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Robust Conditional Probabilities
Poster
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Learning with Bandit Feedback in Potential Games
Poster
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On Blackbox Backpropagation and Jacobian Sensing
Poster
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Communication-Efficient Distributed Learning of Discrete Distributions
Poster
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Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Poster
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When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness
Poster
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Matrix Norm Estimation from a Few Entries
Poster
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Deep Networks for Decoding Natural Images from Retinal Signals
Poster
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Causal Effect Inference with Deep Latent Variable Models
Poster
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Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity
Poster
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Gradient Episodic Memory for Continuum Learning
Poster
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Radon Machines: Effective Parallelisation for Machine Learning
Poster
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Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding
Poster
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Clustering Stable Instances of Euclidean k-means.
Poster
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Good Semi-supervised Learning That Requires a Bad GAN
Poster
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Protein Interface Prediction using Graph Convolutional Networks
Poster
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Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities
Poster
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Towards Generalization and Simplicity in Continuous Control
Poster
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Random Projection Filter Bank for Time Series Data
Poster
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Filtering Variational Objectives
Poster
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On Frank-Wolfe and Equilibrium Computation
Poster
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Modulating early visual processing by language
Poster
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Learning Mixture of Gaussians with Streaming Data
Poster
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Practical Hash Functions for Similarity Estimation and Dimensionality Reduction
Poster
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Two Time-Scale Update Rule for Generative Adversarial Nets
Poster
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The Scaling Limit of High-Dimensional Online Independent Component Analysis
Poster
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Spectral Mixture Kernels for Multi-Output Gaussian Processes
Poster
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Approximation Algorithms for $\ell_0$-Low Rank Approximation
Poster
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The power of absolute discounting: all-dimensional distribution estimation
Poster
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Supervised Adversarial Domain Adaptation
Poster
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Thalamus Gated Recurrent Modules
Poster
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Neural Expectation Maximization
Poster
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Online Learning of Linear Dynamical Systems
Poster
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Z-Forcing: Training Stochastic Recurrent Networks
Poster
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Neural Variational Inference and Learning in Undirected Graphical Models
Poster
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Subspace Clustering via Tangent Cones
Poster
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The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process
Poster
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Acceleration and Averaging in Stochastic Descent Dynamics
Poster
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Inverse Reward Design
Poster
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Structured Bayesian Pruning via Log-Normal Multiplicative Noise
Poster
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Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
Poster
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Kernel functions based on triplet comparisons
Poster
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An Error Detection and Correction Framework for Connectomics
Poster
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Style Transfer from Non-parallel Text by Cross-Alignment
Poster
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Cross-Spectral Factor Analysis
Poster
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Stochastic Submodular Maximization: The Case of Coverage Functions
Poster
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On Distributed Hierarchical Clustering
Poster
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Unsupervised Transformation Learning via Convex Relaxations
Poster
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A Sharp Error Analysis for the Fused Lasso, with Implications to Broader Settings and Approximate Screening
Poster
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Efficient Computation of Moments in Sum-Product Networks
Poster
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A Meta-Learning Perspective on Cold-Start Recommendations for Items
Poster
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Predicting Scene Parsing and Motion Dynamics in the Future
Poster
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Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference
Poster
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Efficient Approximation Algorithms for Strings Kernel Based Sequence Classification
Poster
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Kernel Feature Selection via Conditional Covariance Minimization
Poster
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Statistical Convergence Analysis of Gradient EM on General Gaussian Mixture Models
Poster
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Real Time Image Saliency for Black Box Classifiers
Poster
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Houdini: Democratizing Adversarial Examples
Poster
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Efficient and Flexible Inference for Stochastic Systems
Poster
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When Cyclic Coordinate Descent Beats Randomized Coordinate Descent
Poster
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Active Learning from Peers
Poster
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Learning Causal Graphs with Latent Variables
Poster
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Learning to Model the Tail
Poster
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Stochastic Mirror Descent for Non-Convex Optimization
Poster
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On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models
Poster
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Maxing and Ranking with Few Assumptions
Poster
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On clustering network-valued data
Poster
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A General Framework for Robust Interactive Learning
Poster
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Multi-view Matrix Factorization for Linear Dynamical System Estimation
Poster
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Online Dynamic Programming
Poster
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Unsupervised Learning of Disentangled Representations from Video
Poster
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On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks
Poster
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Deep Reinforcement Learning from Human Preferences
Poster
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Multi-Information Source Optimization
Poster
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Sobolev Training for Neural Networks
Poster
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Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks
Poster
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Efficient Use of Limited-Memory Resources to Accelerate Linear Learning
Poster
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Learning Active Learning from Data
Poster
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Non-parametric Neural Networks
Poster
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Inverse Filtering for Hidden Markov Models
Poster
Dates n/a. @ None
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
Poster
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Random Permutation Online Isotonic Regression
Poster
Dates n/a. @ None
Deconvolutional Paragraph Representation Learning
Poster
Dates n/a. @ None
The Marginal Value of Adaptive Gradient Methods in Machine Learning
Ashia C Wilson · Rebecca D Roelofs · Mitchell Stern · Nati Srebro · Benjamin Recht
Poster
Dates n/a. @ None
Learning A Structured Optimal Bipartite Graph for Co-Clustering
Feiping Nie · Xiaoqian Wang · Heng Huang
Poster
Dates n/a. @ None
Mapping distinct timescales of functional interactions among brain networks
Mali Sundaresan · Arshed Nabeel · Devarajan Sridharan
Poster
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Triple Generative Adversarial Nets
Chongxuan LI · Kun Xu · Jun Zhu · Bo Zhang
Poster
Dates n/a. @ None
Counterfactual Fairness
Matt Kusner · Joshua Loftus · Chris Russell · Ricardo Silva
Poster
Dates n/a. @ None
Streaming Weak Submodularity: Interpreting Neural Networks on the Fly
Ethan R. Elenberg · Alexandros Dimakis · Moran Feldman · Amin Karbasi
Poster
Dates n/a. @ None
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders
Artur Speiser · Jinyao Yan · Evan Archer · Lars Buesing · Srinivas C Turaga · Jakob H Macke
Poster
Dates n/a. @ None
YASS: Yet Another Spike Sorter
Jin Lee · David E Carlson · Hooshmand Razaghi · Weichi Yao · Georges A Goetz · E.J. Chichilnisky · Espen Hagen · Gaute Einevoll · Liam Paninski
Poster
Dates n/a. @ None
Scalable Levy Process Priors for Spectral Kernel Learning
Phillip A Jang · Andrew Loeb · Matthew Davidow · Andrew Wilson
Poster
Dates n/a. @ None
On Tensor Train Rank Minimization : Statistical Efficiency and Scalable Algorithm
Masaaki Imaizumi · Takanori Maehara · Kohei Hayashi
Poster
Dates n/a. @ None
Structured Generative Adversarial Networks
Hao Zhang · Zhijie Deng · Xiaodan Liang · Jun Zhu · Eric P Xing
Poster
Dates n/a. @ None
Conic Scan Coverage algorithm for nonparametric topic modeling
Mikhail Yurochkin · Aritra Guha · XuanLong Nguyen
Poster
Dates n/a. @ None
Dynamic Routing Between Capsules
Sara Sabour · Nicholas Frosst · Geoffrey E Hinton
Poster
Dates n/a. @ None
Recursive Sampling for the Nystrom Method
Cameron Musco · Christopher Musco
Poster
Dates n/a. @ None
Inferring The Latent Structure of Human Decision-Making from Raw Visual Inputs
Yunzhu Li · Jiaming Song · Stefano Ermon
Poster
Dates n/a. @ None
Diving into the shallows: a computational perspective on large-scale shallow learning
SIYUAN MA · Mikhail Belkin
Poster
Dates n/a. @ None
Joint distribution optimal transportation for domain adaptation
Nicolas Courty · Rémi Flamary · Amaury Habrard · Alain Rakotomamonjy
Poster
Dates n/a. @ None
Reducing Reparameterization Gradient Variance
Andrew Miller · Nick Foti · Alexander D'Amour · Ryan Adams
Poster
Dates n/a. @ None
High-Order Attention Models for Visual Question Answering
Idan Schwartz · Alexander Schwing · Tamir Hazan
Poster
Dates n/a. @ None
Off-policy evaluation for slate recommendation
Adith Swaminathan · Akshay Krishnamurthy · Alekh Agarwal · Miro Dudik · John Langford · Damien Jose · Imed Zitouni
Poster
Dates n/a. @ None
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference
Jonathan Huggins · Ryan Adams · Tamara Broderick
Poster
Dates n/a. @ None
Adaptive Batch Size for Safe Policy Gradients
Matteo Papini · Matteo Pirotta · Marcello Restelli
Poster
Dates n/a. @ None
Collecting Telemetry Data Privately
Bolin Ding · Janardhan Kulkarni · Sergey Yekhanin
Poster
Dates n/a. @ None
Eigen-Distortions of Hierarchical Representations
Alexander Berardino · Valero Laparra · Johannes Ballé · Eero P Simoncelli
Poster
Dates n/a. @ None
Gaussian process based nonlinear latent structure discovery in multivariate spike train data
Anqi Wu · Nicholas Roy · Stephen Keeley · Jonathan W Pillow
Poster
Dates n/a. @ None
Tractability in Structured Probability Spaces
Arthur Choi · Yujia Shen · Adnan Darwiche
Poster
Dates n/a. @ None
On Optimal Generalizability in Parametric Learning
Ahmad Beirami · Meisam Razaviyayn · Shahin Shahrampour · Vahid Tarokh
Poster
Dates n/a. @ None
Process-constrained batch Bayesian optimisation
Pratibha Vellanki · Santu Rana · Sunil Gupta · David Rubin · Alessandra Sutti · Thomas Dorin · Murray Height · Paul Sanders · Svetha Venkatesh
Poster
Dates n/a. @ None
A Universal Analysis of Large-Scale Regularized Least Squares Solutions
Ashkan Panahi · Babak Hassibi
Poster
Dates n/a. @ None
Clustering Billions of Reads for DNA Data Storage
Cyrus Rashtchian · Konstantin Makarychev · Luis Ceze · Karin Strauss · Sergey Yekhanin · Djordje Jevdjic · Miklos Racz · Siena Ang
Poster
Dates n/a. @ None
A Regularized Framework for Sparse and Structured Neural Attention
Vlad Niculae · Mathieu Blondel
Poster
Dates n/a. @ None
Utile Context Tree Weighting
Joao V Messias · Shimon Whiteson
Poster
Dates n/a. @ None
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Akash Srivastava · Lazar Valkoz · Chris Russell · Michael Gutmann · Charles Sutton
Poster
Dates n/a. @ None
Bayesian Compression for Deep Learning
Christos Louizos · Karen Ullrich · Max Welling
Poster
Dates n/a. @ None
Language modeling with recurrent highway hypernetworks
Joseph A Suarez
Poster
Dates n/a. @ None
Wasserstein Learning of Deep Generative Point Process Models
SHUAI XIAO · Mehrdad Farajtabar · Xiaojing Ye · Junchi Yan · Le Song · Hongyuan Zha
Poster
Dates n/a. @ None
Differentially private Bayesian learning on distributed data
Mikko Heikkilä · Eemil Lagerspetz · Samuel Kaski · Kana Shimizu · Sasu Tarkoma · Antti Honkela
Poster
Dates n/a. @ None
Graph Matching via Multiplicative Update Algorithm
Bo Jiang · Jin Tang · Bin Luo
Poster
Dates n/a. @ None
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee
Alireza Aghasi · Nam H Nguyen · Justin Romberg
Poster
Dates n/a. @ None
Adversarial Ranking for Language Generation
Dianqi Li · Kevin Lin · Xiaodong He · Ming-ting Sun · Zhengyou Zhang
Poster
Dates n/a. @ None
Partial Hard Thresholding: A Towards Unified Analysis of Support Recovery
Jie Shen · Ping Li
Poster
Dates n/a. @ None
Adaptive Accelerated Gradient Converging Method under H\"{o}lderian Error Bound Condition
Mingrui Liu · Tianbao Yang
Poster
Dates n/a. @ None
Unbiased estimates for linear regression via volume sampling
Michal Derezinski · Manfred K Warmuth
Poster
Dates n/a. @ None
Tomography of the London Underground: a Scalable Model for Origin-Destination Data
Nicolò Colombo · Ricardo Silva · soong Kang
Poster
Dates n/a. @ None
Minimax Optimal Players for the Finite-Time 3-Expert Prediction Problem
Yasin Abbasi · Peter Bartlett · Victor Gabillon
Poster
Dates n/a. @ None
Learning Causal Structures Using Regression Invariance
AmirEmad Ghassami · Saber Salehkaleybar · Negar Kiyavash · Kun Zhang
Poster
Dates n/a. @ None
Continual Learning with Deep Generative Replay
Hanul Shin · Jung Lee · Jaehong Kim · Jiwon Kim
Poster
Dates n/a. @ None
Variance-based Regularization with Convex Objectives
Hongseok Namkoong · John C Duchi
Poster
Dates n/a. @ None
Model-Powered Conditional Independence Test
Rajat Sen · Ananda Suresh · Karthikeyan Shanmugam · Alexandros Dimakis · Sanjay Shakkottai
Poster
Dates n/a. @ None
Beyond Parity: Fairness Objectives for Collaborative Filtering
Sirui Yao · Bert Huang
Poster
Dates n/a. @ None
Gauging Variational Inference
Sung-Soo Ahn · Michael Chertkov · Jinwoo Shin
Poster
Dates n/a. @ None
Mean Field Residual Networks: On the Edge of Chaos
Ge Yang
Poster
Dates n/a. @ None
Convolutional Gaussian Processes
Mark van der Wilk · Carl Edward Rasmussen · James Hensman
Poster
Dates n/a. @ None
Cold-Start Reinforcement Learning with Softmax Policy Gradients
Nan Ding · Radu Soricut
Poster
Dates n/a. @ None
A Bayesian Data Augmentation Approach for Learning Deep Models
Toan M Tran · Trung T Pham · Gustavo Carneiro · Lyle Palmer · Ian Reid
Poster
Dates n/a. @ None
Bridging the Gap Between Value and Policy Based Reinforcement Learning
Ofir Nachum · Mohammad Norouzi · Kelvin Xu · Dale Schuurmans
Poster
Dates n/a. @ None
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning
Haoran Tang · Pieter Abbeel · Davis J Foote · Yan Duan · OpenAI Xi Chen · Rein Houthooft · Adam Stooke · Filip DeTurck
Poster
Dates n/a. @ None
Variational Inference via $\chi$ Upper Bound Minimization
Adji Bousso Dieng · Dustin Tran · Rajesh Ranganath · John Paisley · David Blei
Poster
Dates n/a. @ None
Multi-agent Predictive Modeling with Attentional CommNets
Yedid Hoshen
Poster
Dates n/a. @ None
Dynamic Revenue Sharing
Santiago Balseiro · Max Lin · Vahab Mirrokni · Renato Leme · IIIS Song Zuo
Poster
Dates n/a. @ None
Dual Discriminator Generative Adversarial Nets
Tu Nguyen · Trung Le · Hung Vu · Dinh Phung
Poster
Dates n/a. @ None
Parallel Streaming Wasserstein Barycenters
Matthew Staib · Sebastian Claici · Justin M Solomon · Stefanie Jegelka
Poster
Dates n/a. @ None
Nonlinear random matrix theory for deep learning
Jeffrey Pennington · Pratik Worah
Poster
Dates n/a. @ None
Practical Data-Dependent Metric Compression with Provable Guarantees
Piotr Indyk · Ilya Razenshteyn · Tal Wagner
Poster
Dates n/a. @ None
Multi-way Interacting Regression via Factorization Machines
Mikhail Yurochkin · XuanLong Nguyen · nikolaos Vasiloglou
Poster
Dates n/a. @ None
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning
Justin Fu · John Co-Reyes · Sergey Levine
Poster
Dates n/a. @ None
Fitting Low-Rank Tensors in Constant Time
Kohei Hayashi · Yuichi Yoshida
Poster
Dates n/a. @ None
Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications
Linus Hamilton · Frederic Koehler · Ankur Moitra
Poster
Dates n/a. @ None
Noise-Tolerant Interactive Learning Using Pairwise Comparisons
Yichong Xu · Hongyang Zhang · Aarti Singh · Artur Dubrawski · Kyle Miller
Poster
Dates n/a. @ None
Scalable Demand-Aware Recommendation
Jinfeng Yi · Cho-Jui Hsieh · Kush R Varshney · Lijun Zhang · University of California Yao Li
Poster
Dates n/a. @ None
Collaborative PAC Learning
Avrim Blum · Nika Haghtalab · Ariel D Procaccia · IIIS Mingda Qiao
Poster
Dates n/a. @ None
Non-convex Finite-Sum Optimization Via SCSG Methods
Lihua Lei · Cheng Ju · Jianbo Chen · Michael Jordan
Poster
Dates n/a. @ None
Masked Autoregressive Flow for Density Estimation
George Papamakarios · Iain Murray · Theo Pavlakou
Poster
Dates n/a. @ None
Differentiable Learning of Logical Rules for Knowledge Base Reasoning
Fan Yang · Zhilin Yang · William W Cohen
Poster
Dates n/a. @ None
Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences
Kinjal Basu · Ankan Saha · Shaunak Chatterjee
Poster
Dates n/a. @ None
Associative Embedding: End-to-End Learning for Joint Detection and Grouping
Alejandro Newell · Zhiao Huang · Jia Deng
Poster
Dates n/a. @ None
Few-Shot Learning Through an Information Retrieval Lens
Eleni Triantafillou · Richard Zemel · Raquel Urtasun
Poster
Dates n/a. @ None
Zap Q-Learning
Adithya M Devraj · Sean P Meyn
Poster
Dates n/a. @ None
Runtime Neural Pruning
Ji Lin · Yongming Rao · Jiwen Lu
Poster
Dates n/a. @ None
Backprop without Learning Rates Through Coin Betting
Francesco Orabona · Tatiana Tommasi
Poster
Dates n/a. @ None
Bandits Dueling on Partially Ordered Sets
CMLA Julien Audiffren · Liva Ralaivola
Poster
Dates n/a. @ None
Consistent Robust Regression
Kush Bhatia · Prateek Jain · Purushottam Kar
Poster
Dates n/a. @ None
Neural Program Meta-Induction
Jacob Devlin · Rudy R Bunel · Rishabh Singh · Matthew Hausknecht · Pushmeet Kohli
Poster
Dates n/a. @ None
Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs
Rowan McAllister · Carl Edward Rasmussen
Poster
Dates n/a. @ None
Stabilizing Training of Generative Adversarial Networks through Regularization
Kevin Roth · Aurelien Lucchi · Sebastian Nowozin · Thomas Hofmann
Poster
Dates n/a. @ None
Fast Alternating Minimization Algorithms for Dictionary Learning
Niladri Chatterji · Peter Bartlett
Poster
Dates n/a. @ None
PixelGAN Autoencoders
Alireza Makhzani · Brendan J Frey
Poster
Dates n/a. @ None
Generating steganographic images via adversarial training
Jamie Hayes · George Danezis
Poster
Dates n/a. @ None
Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimization
Pan Xu · Jian Ma · Quanquan Gu
Poster
Dates n/a. @ None
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts
Raymond Yeh · Jinjun Xiong · Wen-Mei Hwu · Minh Do · Alexander Schwing
Poster
Dates n/a. @ None
Lookahead Bayesian Optimization with Inequality Constraints
Remi Lam · Karen Willcox
Poster
Dates n/a. @ None
Revenue Optimization with Approximate Bid Predictions
Andres Munoz · Sergei Vassilvitskii
Poster
Dates n/a. @ None
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
Luigi Acerbi · Wei Ji
Poster
Dates n/a. @ None
Deliberation Networks: Sequence Generation Beyond One-Pass Decoding
Yingce Xia · Lijun Wu · Jianxin Lin · Fei Tian · Tao Qin · Tie-Yan Liu
Poster
Dates n/a. @ None
Minimal Exploration in Structured Stochastic Bandits
Stefan Magureanu · Richard Combes · Alexandre Proutiere
Poster
Dates n/a. @ None
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks
Arjun K Bansal · William Constable · Oguz Elibol · Stewart Hall · Luke Hornof · Amir Khosrowshahi · Carey Kloss · Urs Köster · Marcel Nassar · Naveen Rao · Xin Wang · Tristan Webb
Poster
Dates n/a. @ None
What-If Reasoning using Counterfactual Gaussian Processes
Peter Schulam · Suchi Saria
Poster
Dates n/a. @ None
Predicting User Activity Level In Point Process Models With Mass Transport Equation
Yichen Wang · Xiaojing Ye · Hongyuan Zha · Le Song
Poster
Dates n/a. @ None
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure
Alberto Bietti · Julien Mairal
Poster
Dates n/a. @ None
Deep Hyperalignment
Muhammad Yousefnezhad · Daoqiang Zhang
Poster
Dates n/a. @ None
Cost efficient gradient boosting
Sven Peter · Ferran Diego · Fred Hamprecht · Boaz Nadler
Poster
Dates n/a. @ None
Linear regression without correspondence
Daniel Hsu · Kevin Shi · Xiaorui Sun
Poster
Dates n/a. @ None
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning
Wei Wen · Cong Xu · Feng Yan · Chunpeng Wu · Yandan Wang · Yiran Chen · Hai Li
Poster
Dates n/a. @ None
Best Response Regression
Omer Ben Porat · Moshe Tennenholtz
Poster
Dates n/a. @ None
From which world is your graph
Cheng Li · Varun Kanade · Felix MF Wong · Zhenming Liu
Poster
Dates n/a. @ None
Cognitive Impairment Prediction in Alzheimer’s Disease with Regularized Modal Regression
Xiaoqian Wang · Hong Chen · Dinggang Shen · Heng Huang
Poster
Dates n/a. @ None
Online Convex Optimization with Stochastic Constraints
Hao Yu · Michael Neely · Xiaohan Wei
Poster
Dates n/a. @ None
Nonbacktracking Bounds on the Influence in Independent Cascade Models
Emmanuel Abbe · Sanjeev Kulkarni · Eun Lee
Poster
Dates n/a. @ None
Generalized Linear Model Regression under Distance-to-set Penalties
Jason Xu · Eric Chi · Kenneth Lange
Poster
Dates n/a. @ None
Deanonymization in the Bitcoin P2P Network
Giulia Fanti · Pramod Viswanath
Poster
Dates n/a. @ None
Testing and Learning on Distributions with Symmetric Noise Invariance
Law Ho Chung · Christopher Yau · Dino Sejdinovic
Poster
Dates n/a. @ None
Online Prediction with Selfish Experts
Tim Roughgarden · Okke Schrijvers
Poster
Dates n/a. @ None
Adaptive Bayesian Sampling with Monte Carlo EM
Anirban Roychowdhury · Srinivasan Parthasarathy
Poster
Dates n/a. @ None
Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets
Karol Hausman · Yevgen Chebotar · Stefan Schaal · Gaurav Sukhatme · Joseph J Lim
Poster
Dates n/a. @ None
Matching neural paths: transfer from recognition to correspondence search
Nikolay Savinov · Lubor Ladicky · Marc Pollefeys
Poster
Dates n/a. @ None
Posterior sampling for reinforcement learning: worst-case regret bounds
Shipra Agrawal · Randy Jia
Poster
Dates n/a. @ None
Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data
Stéphanie ALLASSONNIERE · Juliette Chevallier
Poster
Dates n/a. @ None
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations
Eirikur Agustsson · Fabian Mentzer · Michael Tschannen · Lukas Cavigelli · Radu Timofte · Luca Benini · Luc V Gool
Poster
Dates n/a. @ None
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition
Naoya Takeishi · Yoshinobu Kawahara · Takehisa Yairi
Poster
Dates n/a. @ None
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Simon Du · Chi Jin · Jason D Lee · Michael Jordan · Aarti Singh · Barnabas Poczos
Poster
Dates n/a. @ None
Question Asking as Program Generation
Anselm Rothe · Brenden Lake · Todd Gureckis
Poster
Dates n/a. @ None
Inductive Representation Learning on Large Graphs
Will Hamilton · Zhitao Ying · Jure Leskovec
Poster
Dates n/a. @ None
Active Bias: Training a More Accurate Neural Network by Emphasizing High Variance Samples
UMass Haw-Shiuan Chang · Andrew McCallum · Erik Learned-Miller
Poster
Dates n/a. @ None
Learning to Pivot with Adversarial Networks
Gilles Louppe · Michael Kagan · Kyle Cranmer
Poster
Dates n/a. @ None
Decoupling "when to update" from "how to update"
Eran Malach · Shai Shalev-Shwartz
Poster
Dates n/a. @ None
Learning Overcomplete HMMs
Vatsal Sharan · Sham Kakade · Percy S Liang · Gregory Valiant
Poster
Dates n/a. @ None
Safe Model-based Reinforcement Learning with Stability Guarantees
Felix Berkenkamp · Matteo Turchetta · Angela Schoellig · Andreas Krause
Poster
Dates n/a. @ None
Detrended Partial Cross Correlation for Brain Connectivity Analysis
Jaime Ide · Fábio Cappabianco · Fabio Faria · Chiang-shan R Li
Poster
Dates n/a. @ None
Compression-aware Training of Deep Neural Networks
Jose Alvarez · Mathieu Salzmann
Poster
Dates n/a. @ None
Label Distribution Learning Forests
Wei Shen · KAI ZHAO · Yilu Guo · Alan Yuille
Poster
Dates n/a. @ None
Minimizing a Submodular Function from Samples
Eric Balkanski · Yaron Singer
Poster
Dates n/a. @ None
Robust Hypothesis Test for Functional Effect with Gaussian Processes
Jeremiah Liu · Brent Coull
Poster
Dates n/a. @ None
Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees
Francesco Locatello · Michael Tschannen · Gunnar Raetsch · Martin Jaggi
Poster
Dates n/a. @ None
One-Sided Unsupervised Domain Mapping
Sagie Benaim · Lior Wolf
Poster
Dates n/a. @ None
Improved Dynamic Regret for Non-degeneracy Functions
Lijun Zhang · Tianbao Yang · Jinfeng Yi · Rong Jin · Zhi-Hua Zhou
Poster
Dates n/a. @ None
Coded Distributed Computing for Inverse Problems
Yaoqing Yang · Pulkit Grover · Soummya Kar
Poster
Dates n/a. @ None
Safe and Nested Subgame Solving for Imperfect-Information Games
Noam Brown · Tuomas Sandholm
Poster
Dates n/a. @ None
Diffusion Approximations for Online Principal Component Estimation and Global Convergence
Chris Junchi Li · Mengdi Wang · Tong Zhang
Poster
Dates n/a. @ None
Efficient Online Linear Optimization with Approximation Algorithms
Dan Garber
Poster
Dates n/a. @ None
Hypothesis Transfer Learning via Transformation Functions
Simon Du · Jayanth Koushik · Aarti Singh · Barnabas Poczos
Poster
Dates n/a. @ None
Multimodal Learning and Reasoning for Visual Question Answering
Ilija Ilievski · Jiashi Feng
Poster
Dates n/a. @ None
Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions
Ryan J Tibshirani
Poster
Dates n/a. @ None
Learning multiple visual domains with residual adapters
Sylvestre-Alvise Rebuffi · Hakan Bilen · Andrea Vedaldi
Poster
Dates n/a. @ None
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms
An Bian · Joachim M Buhmann · Andreas Krause · Kfir Levy
Poster
Dates n/a. @ None
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems
Simon Du · Yining Wang · Aarti Singh
Poster
Dates n/a. @ None
Preventing Gradient Explosions in Gated Recurrent Units
Sekitoshi Kanai · Yasuhiro Fujiwara · Sotetsu Iwamura
Poster
Dates n/a. @ None
On the Model Shrinkage Effect of Gamma Process Edge Partition Models
Iku Ohama · Issei Sato · Takuya Kida · Hiroki Arimura
Poster
Dates n/a. @ None
Phase Transitions in the Pooled Data Problem
Jonathan Scarlett · Volkan Cevher
Poster
Dates n/a. @ None
Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks
Wei-Sheng Lai · Jia-Bin Huang · Ming-Hsuan Yang
Poster
Dates n/a. @ None
Gated Recurrent Convolution Neural Network for OCR
Jianfeng Wang · Xiaolin Hu
Poster
Dates n/a. @ None
Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model
Jiasen Lu · Anitha Kannan · Jianwei Yang · Dhruv Batra · Devi Parikh
Poster
Dates n/a. @ None
A simple model of recognition and recall memory
Nisheeth Srivastava · Edward Vul
Poster
Dates n/a. @ None
Cortical microcircuits as gated-recurrent neural networks
Rui Costa · Ioannis Alexandros Assael · Brendan Shillingford · Nando de Freitas · TIm Vogels
Poster
Dates n/a. @ None
Structured Embedding Models for Grouped Data
Maja Rudolph · Francisco Ruiz · David Blei
Poster
Dates n/a. @ None
From Parity to Preference: Learning with Cost-effective Notions of Fairness
Muhammad Bilal Zafar · Isabel Valera · Manuel Rodriguez · Krishna Gummadi · Adrian Weller
Poster
Dates n/a. @ None
Uprooting and Rerooting Higher-order Graphical Models
Adrian Weller · Mark Rowland
Poster
Dates n/a. @ None
Parametric Simplex Method for Sparse Learning
Haotian Pang · Tuo Zhao · Han Liu · Robert Vanderbei
Poster
Dates n/a. @ None
Interactive Submodular Bandit
Lin Chen · Andreas Krause · Amin Karbasi
Poster
Dates n/a. @ None
Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent
Peva Blanchard · El Mahdi El Mhamdi · Rachid Guerraoui · Julien Stainer
Poster
Dates n/a. @ None
Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs
Saurabh Verma · Zhi-Li Zhang
Poster
Dates n/a. @ None
Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis
Jian Zhao · Lin Xiong · Panasonic Karlekar Jayashree · Jianshu Li · Fang Zhao · Zhecan Wang · Panasonic Sugiri Pranata · Panasonic Shengmei Shen · Jiashi Feng
Poster
Dates n/a. @ None
Rethinking Feature Discrimination and Polymerization for Large-scale Recognition
Yu Liu · Hongyang Li · Xiaogang Wang
Poster
Dates n/a. @ None
Attentional Pooling for Action Recognition
Rohit Girdhar · Deva Ramanan
Poster
Dates n/a. @ None
Wider and Deeper, Cheaper and Faster: Tensorized LSTMs for Sequence Learning
Zhen He · Shaobing Gao · Liang Xiao · David Barber
Poster
Dates n/a. @ None
Learning Low-Dimensional Metrics
Blake Mason · Lalit Jain · Robert Nowak
Poster
Dates n/a. @ None
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification
Bikash Joshi · Massih-Reza Amini · Ioannis Partalas · Franck Iutzeler · Yury Maximov
Poster
Dates n/a. @ None
Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression
Shinji Ito · Akihiro Yabe · Ken-Ichi Kawarabayashi · Naonori Kakimura · Takuro Fukunaga · Daisuke Hatano · Hanna Sumita
Poster
Dates n/a. @ None
Multi-Armed Bandits with Metric Movement Costs
Tomer Koren · Roi Livni · Yishay Mansour
Poster
Dates n/a. @ None
Successor Features for Transfer in Reinforcement Learning
Andre Barreto · Will Dabney · Remi Munos · Jonathan Hunt · Tom Schaul · David Silver · Hado van Hasselt
Poster
Dates n/a. @ None
Prototypical Networks for Few-shot Learning
Jake Snell · Kevin Swersky · Richard Zemel
Poster
Dates n/a. @ None
Independence clustering (without a matrix)
Daniil Ryabko
Poster
Dates n/a. @ None
Adaptive Active Hypothesis Testing under Limited Information
Fabio Cecchi · Nidhi Hegde
Poster
Dates n/a. @ None
Deep Hyperspherical Learning
Weiyang Liu · Institute of Automation yan-Ming Zhang · Xingguo Li · Zhiding Yu · Bo Dai · Tuo Zhao · Le Song
Poster
Dates n/a. @ None
On-the-fly Operation Batching in Dynamic Computation Graphs
Graham Neubig · Yoav Goldberg · Chris Dyer
Poster
Dates n/a. @ None
Learning Deep Structured Multi-Scale Features using Attention-Gated CRFs for Contour Prediction
Dan Xu · Wanli Ouyang · Xavier Alameda-Pineda · Elisa Ricci · Xiaogang Wang · Nicu Sebe
Poster
Dates n/a. @ None
Conservative Contextual Linear Bandits
Abbas Kazerouni · Mohammad Ghavamzadeh · Yasin Abbasi · Benjamin Van Roy
Poster
Dates n/a. @ None
Variational Memory Addressing in Generative Models
Jörg Bornschein · Andriy Mnih · Daniel Zoran · Danilo Jimenez Rezende
Poster
Dates n/a. @ None
Incorporating Side Information by Adaptive Convolution
Di Kang · Debarun Dhar · Antoni B Chan
Poster
Dates n/a. @ None
FALKON: An Optimal Large Scale Kernel Method
Alessandro Rudi · Luigi Carratino · Lorenzo Rosasco
Poster
Dates n/a. @ None
Variational Laws of Visual Attention for Dynamic Scenes
Dario Zanca · Marco Gori
Poster
Dates n/a. @ None
Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning
Shixiang Gu · Tim Lillicrap · Richard E Turner · Zoubin Ghahramani · Bernhard Schölkopf · Sergey Levine
Poster
Dates n/a. @ None
End-to-end Differentiable Proving
Tim Rocktäschel · Sebastian Riedel
Poster
Dates n/a. @ None
Nonlinear Acceleration of Stochastic Algorithms
Damien Scieur · Francis Bach · Alexandre d'Aspremont
Poster
Dates n/a. @ None
Influence Maximization with $\varepsilon$-Almost Submodular Threshold Function
Qiang Li · Wei Chen · Institute of Computing Xiaoming Sun · Institute of Computing Jialin Zhang
Poster
Dates n/a. @ None
Universal consistency and minimax rates for online Mondrian Forest
Jaouad Mourtada · Stéphane Gaïffas · Erwan Scornet
Poster
Dates n/a. @ None
Collapsed variational Bayes for Markov jump processes
Boqian Zhang · Jiangwei Pan · Vinayak A Rao
Poster
Dates n/a. @ None
Working hard to know your neighbor's margins: Local descriptor learning loss
Poster
Dates n/a. @ None
Efficiency Guarantees from Data
Darrell Hoy · Denis Nekipelov · Vasilis Syrgkanis
Poster
Dates n/a. @ None
Visual Reference Resolution using Attention Memory for Visual Dialog
Paul Seo · Andreas Lehrmann · Bohyung Han · Leonid Sigal
Poster
Dates n/a. @ None
Multiresolution Kernel Approximation for Gaussian Process Regression
Yi Ding · Risi Kondor · Jonathan Eskreis-Winkler
Poster
Dates n/a. @ None
Quantifying how much sensory information in a neural code is relevant for behavior
Giuseppe Pica · Eugenio Piasini · Houman Safaai · Caroline Runyan · Christopher Harvey · Mathew Diamond · Christoph Kayser · Stefano Panzeri · Tommaso Fellin
Poster
Dates n/a. @ None
Sparse convolutional coding for neuronal assembly detection
Sven Peter · Elke Kirschbaum · Martin Both · Intramural Lee Campbell · Intramural Brandon Harvey · Intramural Conor Heins · Daniel Durstewitz · Ferran Diego · Fred Hamprecht
Poster
Dates n/a. @ None
Deep adversarial neural decoding
Poster
Dates n/a. @ None
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks
Federico Monti · Michael Bronstein · Xavier Bresson
Poster
Dates n/a. @ None
Bayesian GANs
Yunus Saatci · Andrew Wilson
Poster
Dates n/a. @ None
A multi-agent reinforcement learning model of common-pool resource appropriation
Julien Pérolat · Joel Leibo · Vinicius Zambaldi · Charles Beattie · Karl Tuyls · Thore Graepel
Poster
Dates n/a. @ None
Concrete Dropout
Yarin Gal · George Hron · Alex Kendall
Poster
Dates n/a. @ None
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning
Marco Fraccaro · Simon Kamronn · Ulrich Paquet · Ole Winther
Poster
Dates n/a. @ None
Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums Optimization
Yossi Arjevani
Poster
Dates n/a. @ None
Subset Selection under Noise
Chao Qian · Jing-Cheng Shi · Yang Yu · Ke Tang · Zhi-Hua Zhou
Poster
Dates n/a. @ None
Unsupervised Sequence Classification using Sequential Output Statistics
Yu Liu · Jianshu Chen · Li Deng
Poster
Dates n/a. @ None
Neural system identification for large populations separating "what" and "where"
David Klindt · Alexander Ecker · Thomas Euler · Matthias Bethge
Poster
Dates n/a. @ None
Certified Defenses for Data Poisoning Attacks
Jacob Steinhardt · Pang Wei W Koh · Percy S Liang
Poster
Dates n/a. @ None
Near Optimal Sketching of Low-Rank Tensor Regression
Xingguo Li · Jarvis Haupt · David Woodruff
Poster
Dates n/a. @ None
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit
Laurence Aitchison · Lloyd Russell · Adam Packer · Jinyao Yan · Philippe Castonguay · Michael Hausser · Srinivas C Turaga
Poster
Dates n/a. @ None
Spherical convolutions and their application in molecular modelling
Wouter Boomsma · Jes Frellsen
Poster
Dates n/a. @ None
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes
Ahmed Ibrahim · Mihaela van der Schaar
Poster
Dates n/a. @ None
VAE Learning via Stein Variational Gradient Descent
Poster
Dates n/a. @ None
Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding
Wenbing Huang · Fuchun Sun · Tong Zhang · Junzhou Huang · Mehrtash Harandi
Poster
Dates n/a. @ None
Deep Sets
Manzil Zaheer · Satwik Kottur · Mohsen Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola
Poster
Dates n/a. @ None
ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events
MILA Tegan Maharaj · Evan Racah · Christopher J Beckham · Mr. Prabhat · Chris Pal
Poster
Dates n/a. @ None
Multi-output Polynomial Networks and Factorization Machines
Mathieu Blondel · Vlad Niculae · Takuma Otsuka · Naonori Ueda
Poster
Dates n/a. @ None
Multi-Objective Non-parametric Sequential Prediction
Guy Uziel · Ran El-Yaniv
Poster
Dates n/a. @ None
Sparse k-Means Embedding
Weiwei Liu · Xiaobo Shen · Ivor Tsang
Poster
Dates n/a. @ None
Optimized Pre-Processing for Discrimination Prevention
Flavio Calmon · Dennis Wei · Karthikeyan Ramamurthy · Bhanukiran Vinzamuri · Kush R Varshney
Poster
Dates n/a. @ None
Searching in the Dark: Practical SVRG Methods under Error Bound Conditions with Guarantee
Yi Xu · Univ Qihang Lin · Tianbao Yang
Poster
Dates n/a. @ None
Streaming Sparse Gaussian Process Approximations
Thang D Bui · Cuong Nguyen · Richard E Turner
Poster
Dates n/a. @ None
Learning to Compose Domain-Specific Transformations for Data Augmentation
Alexander Ratner · Henry Ehrenberg · Zeshan Hussain · Jared Dunnmon · Christopher Ré
Poster
Dates n/a. @ None
Ensemble Sampling
Xiuyuan Lu · Benjamin Van Roy
Poster
Dates n/a. @ None
Is the Bellman residual a bad proxy?
Matthieu Geist · Bilal Piot · Olivier Pietquin
Poster
Dates n/a. @ None
Dynamic Importance Sampling for Anytime Bounds of the Partition Function
Qi Lou · Rina Dechter · Alexander Ihler
Poster
Dates n/a. @ None
On the Optimization Landscape of Tensor Decompositions
Rong Ge · Tengyu Ma
Poster
Dates n/a. @ None
Regret Minimization in MDPs with Options without Prior Knowledge
Ronan Fruit · Matteo Pirotta · Alessandro Lazaric · Emma Brunskill
Poster
Dates n/a. @ None
Generalization Properties of Learning with Random Features
Alessandro Rudi · Lorenzo Rosasco
Poster
Dates n/a. @ None
Stein Variational Gradient Descent as Gradient Flow
Qiang Liu
Poster
Dates n/a. @ None
Shallow Updates for Deep Reinforcement Learning
Nir Levine · Tom Zahavy · Daniel J Mankowitz · Aviv Tamar · Shie Mannor
Poster
Dates n/a. @ None
Rotting Bandits
Nir Levine · Koby Crammer · Shie Mannor
Poster
Dates n/a. @ None
An Applied Algorithmic Foundation for Hierarchical Clustering
Joshua Wang · Benjamin Moseley
Poster
Dates n/a. @ None
Reinforcement Learning under Model Mismatch
Aurko Roy · Huan Xu · Sebastian Pokutta
Poster
Dates n/a. @ None
A Highly Efficient Gradient Boosting Decision Tree
Guolin Ke · Qi Meng · Taifeng Wang · Wei Chen · Weidong Ma · Tie-Yan Liu
Poster
Dates n/a. @ None
Hierarchical Attentive Recurrent Tracking
Adam Kosiorek · Alex Bewley · Ingmar Posner
Poster
Dates n/a. @ None
AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms
Marco Cusumano-Towner · Vikash K Mansinghka
Poster
Dates n/a. @ None
Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback
Zheng Wen · Branislav Kveton · Michal Valko · Sharan Vaswani
Poster
Dates n/a. @ None
Deep Voice 2: Multi-Speaker Neural Text-to-Speech
Andrew Gibiansky
Poster
Dates n/a. @ None
Deep Lattice Networks and Partial Monotonic Functions
Seungil You · David Ding · Kevin Canini · Jan Pfeifer · Maya Gupta
Poster
Dates n/a. @ None
State Aware Imitation Learning
Yannick Schroecker · Charles L Isbell
Poster
Dates n/a. @ None
A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent
Ben London
Poster
Dates n/a. @ None
Decomposable Submodular Function Minimization: Discrete and Continuous
Alina Ene · Huy Nguyen · Laszlo Vegh
Poster
Dates n/a. @ None
Robust Estimation of Neural Signals in Calcium Imaging
Hakan Inan · Murat Erdogdu · Mark Schnitzer
Poster
Dates n/a. @ None
Deep Recurrent Neural Network-Based Identification of Precursor microRNAs
Seunghyun Park · Seonwoo Min · Hyun-soo Choi · Sungroh Yoon
Poster
Dates n/a. @ None
Alternating Estimation for Structured High-Dimensional Multi-Response Models
Sheng Chen · Arindam Banerjee
Poster
Dates n/a. @ None
Estimation of the covariance structure of heavy-tailed distributions
Xiaohan Wei · Stanislav Minsker
Poster
Dates n/a. @ None
Premise Selection for Theorem Proving by Deep Graph Embedding
Mingzhe Wang · Yihe Tang · Jian Wang · Jia Deng
Poster
Dates n/a. @ None
Principles of Riemannian Geometry in Neural Networks
Michael Hauser · Asok Ray
Poster
Dates n/a. @ None
On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning
Xingguo Li · Lin Yang · Jason Ge · Jarvis Haupt · Tong Zhang · Tuo Zhao
Poster
Dates n/a. @ None
An Empirical Study on The Properties of Random Bases for Kernel Methods
Maximilian Alber · Pieter-Jan Kindermans · Kristof Schütt · Klaus-Robert Müller · Fei Sha
Poster
Dates n/a. @ None
Decomposition-Invariant Conditional Gradient for General Polytopes with Line Search
Mohammad Ali Bashiri · Xinhua Zhang
Poster
Dates n/a. @ None
An Empirical Bayes Approach to Optimizing Machine Learning Algorithms
James McInerney
Poster
Dates n/a. @ None
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games
Yuandong Tian · Qucheng Gong · Wenling Shang · Yuxin Wu · C. Lawrence Zitnick
Poster
Dates n/a. @ None
Fully Decentralized Policies for Multi-Agent Systems: An Information Theoretic Approach
Roel Dobbe · David Fridovich-Keil · Claire Tomlin
Poster
Dates n/a. @ None
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker · Andriy Mnih · Chris J Maddison · John Lawson · Jascha Sohl-Dickstein
Poster
Dates n/a. @ None
Differentially Private Empirical Risk Minimization Revisited: Faster and More General
Di Wang · Minwei Ye · Jinhui Xu
Poster
Dates n/a. @ None
Multitask Spectral Learning of Weighted Automata
Guillaume RABUSSEAU · Borja Balle · Joelle Pineau
Poster
Dates n/a. @ None
Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network
Wengong Jin · Connor Coley · Regina Barzilay · Tommi Jaakkola
Poster
Dates n/a. @ None
Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System
Chengxu Zhuang · Jonas Kubilius · Mitra Hartmann · Daniel Yamins
Poster
Dates n/a. @ None
Rigorous Dynamics and Consistent Estimation in Arbitrarily Conditioned Linear Systems
Alyson Fletcher · Sundeep Rangan · Mojtaba Sahraee-Ardakan · Philip Schniter
Poster
Dates n/a. @ None
Exploring Generalization in Deep Learning
Poster
Dates n/a. @ None
Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM
Steven Z. Wu · Bo Waggoner · Seth Neel · Aaron Roth · Katrina Ligett
Poster
Dates n/a. @ None
Information-theoretic analysis of generalization capability of learning algorithms
Maxim Raginsky · Aolin Xu
Poster
Dates n/a. @ None
Fisher GAN
Youssef Mroueh · Tom Sercu
Poster
Dates n/a. @ None
Sparse Approximate Conic Hulls
Greg Van Buskirk · Ben Raichel · Nicholas Ruozzi
Poster
Dates n/a. @ None
Deep supervised discrete hashing
Qi Li · Zhenan Sun · Ran He · Tieniu Tan
Poster
Dates n/a. @ None
How regularization affects the critical points in linear networks
Amirhossein Taghvaei · Jin W Kim · Prashant G Mehta
Poster
Dates n/a. @ None
Using Options and Covariance Testing for Long Horizon Off-Policy Policy Evaluation
Zhaohan Guo · Philip S. Thomas · Emma Brunskill
Poster
Dates n/a. @ None
Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems
Yonatan Belinkov
Poster
Dates n/a. @ None
Generative Local Metric Learning for Kernel Regression
Yung-Kyun Noh · Masashi Sugiyama · Kee-Eung Kim · Frank Park · Daniel Lee
Poster
Dates n/a. @ None
Fast Black-box Variational Inference through Stochastic Trust-Region Optimization
Jeffrey Regier · Michael Jordan · Jon McAuliffe
Poster
Dates n/a. @ None
SGD Learns the Conjugate Kernel Class of the Network
Amit Daniely
Poster
Dates n/a. @ None
Beyond normality: Learning sparse probabilistic graphical models in the non-Gaussian setting
Rebecca Morrison · Ricardo Baptista · Youssef Marzouk
Poster
Dates n/a. @ None
OnACID: Online Analysis of Calcium Imaging Data in Real Time
Andrea Giovannucci · Johannes Friedrich · Matt Kaufman · Anne Churchland · Dmitri Chklovskii · Liam Paninski · Eftychios Pnevmatikakis
Poster
Dates n/a. @ None
Inner-loop free ADMM using Auxiliary Deep Neural Networks
Kai Fan · Qi Wei · Katherine A Heller
Poster
Dates n/a. @ None
Inhomogoenous Hypergraph Clustering with Applications
Pan Li · Olgica Milenkovic
Poster
Dates n/a. @ None
Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks
Ahmed Ibrahim · Mihaela van der Schaar
Poster
Dates n/a. @ None
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation
Matthias Hein · Maksym Andriushchenko
Poster
Dates n/a. @ None
Practical Locally Private Heavy Hitters
kobbi nissim · Raef Bassily · Uri Stemmer · Abhradeep Thakurta
Poster
Dates n/a. @ None
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe
Quentin Berthet · Vianney Perchet
Poster
Dates n/a. @ None
Expectation Propagation for t-Exponential Family Using Q-Algebra
Futoshi Futami · Issei Sato · Masashi Sugiyama
Poster
Dates n/a. @ None
Compressing the Gram Matrix for Learning Neural Networks in Polynomial Time
Surbhi Goel · Adam Klivans
Poster
Dates n/a. @ None
The Reversible Residual Network: Backpropagation Without Storing Activations
Aidan N Gomez · Mengye Ren · Raquel Urtasun · Roger Grosse
Poster
Dates n/a. @ None
MMD GAN: Towards Deeper Understanding of Moment Matching Network
Chun-Liang Li · Wei-Cheng Chang · Yu Cheng · Yiming Yang · Barnabas Poczos
Poster
Dates n/a. @ None
Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols
Serhii Havrylov · Ivan Titov
Poster
Dates n/a. @ None
Pixels to Graphs by Associative Embedding
Alejandro Newell · Jia Deng
Poster
Dates n/a. @ None
Natural value approximators: learning when to trust past estimates
Tom Schaul · Zhongwen Xu · Joseph Modayil · Hado van Hasselt · Andre Barreto · David Silver
Poster
Dates n/a. @ None
Elementary Symmetric Polynomials for Optimal Experimental Design
Zelda E. Mariet · Suvrit Sra
Poster
Dates n/a. @ None
Bayesian Dyadic Trees and Histograms for Regression
Stéphanie van der Pas · Veronika Rockova
Poster
Dates n/a. @ None
A graph-theoretic approach to multitasking
Noga Alon · Daniel Reichman · Igor Shinkar · Tal Wagner · Sebastian Musslick · Tom Griffiths · Jonathan D Cohen · Biswadip dey · Kayhan Ozcimder
Poster
Dates n/a. @ None
Compatible Reward Inverse Reinforcement Learning
Alberto Maria Metelli · Matteo Pirotta · Marcello Restelli
Poster
Dates n/a. @ None
Hiding Images in Plain Sight: Deep Steganography
Google Shumeet Baluja
Poster
Dates n/a. @ None
First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization
Aryan Mokhtari · Alejandro Ribeiro
Poster
Dates n/a. @ None
Learning ReLUs via Gradient Descent
Soltanolkotabi
Poster
Dates n/a. @ None
Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems
Wen Dong · Le Fang · Fan Yang · Tong Guan · Chunming Qiao
Poster
Dates n/a. @ None
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
Jason Altschuler · Jonathan Weed · Philippe Rigollet
Poster
Dates n/a. @ None
Consistent Multitask Learning with Nonlinear Output Relations
Carlo Ciliberto · Alessandro Rudi · Lorenzo Rosasco · Massimiliano Pontil
Poster
Dates n/a. @ None
Revisit Fuzzy Neural Network: Demystifying Batch Normalization and ReLU with Generalized Hamming Network
Lixin Fan
Poster
Dates n/a. @ None
Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models
Sergey Ioffe
Poster
Dates n/a. @ None
Unsupervised Learning of Disentangled Latent Representations from Sequential Data
Wei-Ning Hsu · Yu Zhang · James Glass
Poster
Dates n/a. @ None
Hierarchical Methods of Moments
Matteo Ruffini · Guillaume RABUSSEAU · Borja Balle
Poster
Dates n/a. @ None
Learning Chordal Markov Networks via Branch and Bound
Kari Rantanen · Antti Hyttinen · Matti Järvisalo
Poster
Dates n/a. @ None
Solving (Almost) all Systems of Random Quadratic Equations
Gang Wang · Georgios Giannakis · Yousef Saad · Jie Chen
Poster
Dates n/a. @ None
Repeated Inverse Reinforcement Learning
Kareem Amin · Nan Jiang · Satinder Singh
Poster
Dates n/a. @ None
Log-normality and Skewness of Estimated State/Action Values in Reinforcement Learning
Liangpeng Zhang · Ke Tang · Xin Yao
Poster
Dates n/a. @ None
The Numerics of GANs
Lars Mescheder · Sebastian Nowozin · Andreas Geiger
Poster
Dates n/a. @ None
Learned D-AMP: Principled Neural-network-based Compressive Image Recovery
Christopher Metzler · Ali Mousavi · Richard Baraniuk
Poster
Dates n/a. @ None
Adaptive Clustering through Semidefinite Programming
Martin Royer
Poster
Dates n/a. @ None
Clustering with Noisy Queries
Poster
Dates n/a. @ None
Train longer, generalize better: closing the generalization gap in large batch training of neural networks
Elad Hoffer · Itay Hubara · Daniel Soudry
Poster
Dates n/a. @ None
On the Convergence of Block Coordinate Descent in Training DNNs with Tikhonov Regularization
Ziming Zhang · Matthew Brand
Poster
Dates n/a. @ None
Imagination-Augmented Agents for Deep Reinforcement Learning
Poster
Dates n/a. @ None
Model evidence from nonequilibrium simulations
Michael Habeck
Poster
Dates n/a. @ None
Positive-Unlabeled Learning with Non-Negative Risk Estimator
Ryuichi Kiryo · Gang Niu · Marthinus C du Plessis · Masashi Sugiyama
Poster
Dates n/a. @ None
Deep Dynamic Poisson Factorization Model
Chengyue Gong · win-bin huang
Poster
Dates n/a. @ None
Communication-Efficient Stochastic Gradient Descent, with Applications to Neural Networks
Dan Alistarh · Demjan Grubic · Jerry Li · Ryota Tomioka · Milan Vojnovic
Poster
Dates n/a. @ None
Optimal Sample Complexity of M-wise Data for Top-K Ranking
Minje Jang · Sunghyun Kim · Changho Suh · Sewoong Oh
Poster
Dates n/a. @ None
Deep Learning with Topological Signatures
Christoph Hofer · Roland Kwitt · Marc Niethammer · Andreas Uhl
Poster
Dates n/a. @ None
Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues
Noga Alon · Moshe Babaioff · Yannai Gonczarowski · Yishay Mansour · Shay Moran · Amir Yehudayoff
Poster
Dates n/a. @ None
Learning Multiple Tasks with Deep Relationship Networks
Mingsheng Long · Jianmin Wang · Philip Yu
Poster
Dates n/a. @ None
Online to Offline Conversions and Adaptive Minibatch Sizes
Kfir Levy
Poster
Dates n/a. @ None
Probabilistic Rule Realization and Selection
Haizi Yu · Tianxi Li · Lav R Varshney
Poster
Dates n/a. @ None
A Scale Free Algorithm for Stochastic Bandits with Bounded Kurtosis
Tor Lattimore
Poster
Dates n/a. @ None
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions
Aryeh Kontorovich · Sivan Sabato · Roi Weiss
Poster
Dates n/a. @ None
Learning Affinity via Spatial Propagation Networks
Sifei Liu · Guangyu Zhong · Ming-Hsuan Yang · Shalini De Mello · Jan Kautz · Jinwei Gu
Poster
Dates n/a. @ None
NeuralFDR: Learning Discovery Thresholds from Hypothesis Features
Jinye Zhang · Fei Xia · James Zou · David Tse
Poster
Dates n/a. @ None
A New Alternating Direction Method for Linear Programming
Sinong Wang · Ness Shroff
Poster
Dates n/a. @ None
Regret Analysis for Continuous Dueling Bandit
Wataru Kumagai
Poster
Dates n/a. @ None
Max-Margin Invariant Features from Transformed Unlabelled Data
Dipan Pal · Ashwin Kannan · Gautam Arakalgud · Marios Savvides
Poster
Dates n/a. @ None
Translation Synchronization via Truncated Least Squares
Xiangru Huang · Zhenxiao Liang · Chandrajit Bajaj · Qixing Huang
Poster
Dates n/a. @ None
Adaptive sampling for a population of neurons
Benjamin Cowley · Ryan Williamson · Katerina Clemens · Matthew Smith · Byron M Yu
Poster
Dates n/a. @ None
Learning with Feature Evolvable Streams
Bo-Jian Hou · Lijun Zhang · Zhi-Hua Zhou
Poster
Dates n/a. @ None
A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering
Hongteng Xu · Hongyuan Zha
Poster
Dates n/a. @ None
Accelerated consensus via Min-Sum Splitting
Patrick Rebeschini · Sekhar C Tatikonda
Poster
Dates n/a. @ None
Tensor Biclustering
Soheil Feizi · Hamid Javadi · David Tse
Poster
Dates n/a. @ None
Learning Unknown Markov Decision Processes: A Thompson Sampling Approach
Yi Ouyang · Mukul Gagrani · Ashutosh Nayyar · Rahul Jain
Poster
Dates n/a. @ None
DPSCREEN: Dynamic Personalized Screening
Kartik Ahuja · William Zame · Mihaela van der Schaar
Poster
Dates n/a. @ None
No More Fixed Penalty Parameter in ADMM: Faster Convergence with New Adaptive Penalization
Yi Xu · Mingrui Liu · Tianbao Yang · Univ Qihang Lin
Poster
Dates n/a. @ None
Flexible statistical inference for mechanistic models of neural dynamics
Jan-Matthis Lueckmann · Pedro J Goncalves · Giacomo Bassetto · Kaan Oecal · Marcel Nonnenmacher · Jakob H Macke
Poster
Dates n/a. @ None
Shape and Material from Sound
zhoutong zhang · Qiujia Li · Zhengjia Huang · Jiajun Wu · Josh Tenenbaum · Bill Freeman
Poster
Dates n/a. @ None
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data
Joel A Tropp · Alp Yurtsever · Madeleine Udell · Volkan Cevher
Poster
Dates n/a. @ None
Learning to Inpaint for Image Compression
Mohammad Haris Baig · Vladlen Koltun · Lorenzo Torresani
Poster
Dates n/a. @ None
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen · Harri Valpola
Poster
Dates n/a. @ None
Linearly constrained Gaussian processes
Carl Jidling · Niklas Wahlström · University of Newcastle Adrian Wills · Thomas B Schön
Poster
Dates n/a. @ None
Improving Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms and Its Applications
Qinshi Wang · Wei Chen
Poster
Dates n/a. @ None
Predictive-State Decoders: Encoding the Future into Recurrent Networks
Arun Venkatraman · Nicholas Rhinehart · Wen Sun · Lerrel Pinto · Martial Hebert · Byron Boots · Kris Kitani · J. Bagnell
Poster
Dates n/a. @ None
Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction
Kristofer Bouchard · Alejandro Bujan · Farbod Roosta-Khorasani · Shashanka Ubaru · Mr. Prabhat · Antoine Snijders · Jian-Hua Mao · Edward Chang · Michael W Mahoney · Sharmodeep Bhattacharya
Poster
Dates n/a. @ None
Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding
Mainak Jas · Tom Dupré la Tour · Umut Simsekli · Alexandre Gramfort
Poster
Dates n/a. @ None
One-Shot Imitation Learning
Yan Duan · Marcin Andrychowicz · OpenAI Bradly Stadie · OpenAI Jonathan Ho · Jonas Schneider · Ilya Sutskever · Pieter Abbeel · Wojciech Zaremba
Poster
Dates n/a. @ None
Subset Selection for Sequential Data
Ehsan Elhamifar
Poster
Dates n/a. @ None
Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces
Songbai Yan · Chicheng Zhang
Poster
Dates n/a. @ None
MolecuLeNet: A continuous-filter convolutional neural network for modeling quantum interactions
Kristof Schütt · Pieter-Jan Kindermans · Huziel Sauceda · Stefan Chmiela · Alexandre Tkatchenko · Klaus-Robert Müller
Poster
Dates n/a. @ None
Differentiable Learning of Submodular Functions
Josip Djolonga · Andreas Krause
Poster
Dates n/a. @ None
GP CaKe: Effective brain connectivity with causal kernels
Luca Ambrogioni · Max Hinne · Marcel Van Gerven · Eric Maris
Poster
Dates n/a. @ None
Self-Normalizing Neural Networks
Günter Klambauer · Thomas Unterthiner · Andreas Mayr · Sepp Hochreiter
Poster
Dates n/a. @ None
Contrastive Learning for Image Captioning
Bo Dai · Dahua Lin
Poster
Dates n/a. @ None
Online multiclass boosting
Young Hun Jung · Jack Goetz · Ambuj Tewari
Poster
Dates n/a. @ None
Multiscale Semi-Markov Dynamics for Intracortical Brain-Computer Interfaces
Daniel Milstein · Jason Pacheco · Brown Leigh Hochberg · Brown John Simeral · Beata Jarosiewicz · Erik Sudderth
Poster
Dates n/a. @ None
Matching on Balanced Nonlinear Representations for Treatment Effects Estimation
Sheng Li · Yun Fu
Poster
Dates n/a. @ None
PredRNN: Recurrent Neural Networks for Video Prediction using Spatiotemporal LSTMs
Yunbo Wang · Mingsheng Long · Jianmin Wang · Philip Yu
Poster
Dates n/a. @ None
Introspective Classification with Convolutional Nets
Long Jin · Justin Lazarow · Zhuowen Tu
Poster
Dates n/a. @ None
Unsupervised object learning from dense equivariant image labelling
James Thewlis · Andrea Vedaldi · Hakan Bilen
Poster
Dates n/a. @ None
A New Theory for Nonconvex Matrix Completion
Guangcan Liu · Xiaotong Yuan · Qingshan Liu
Poster
Dates n/a. @ None
Lower bounds on the robustness to adversarial perturbations
Jonathan Peck · Yvan Saeys · Bart Goossens · Joris Roels
Poster
Dates n/a. @ None
Learning Efficient Object Detection Models with Knowledge Distillation
Guobin Chen · Wongun Choi · Xiang Yu · Tony Han · Manmohan Chandraker
Poster
Dates n/a. @ None
Deep Mean-Shift Priors for Image Restoration
Siavash Arjomand Bigdeli · Matthias Zwicker · Paolo Favaro · Meiguang Jin
Poster
Dates n/a. @ None
Unsupervised Image-to-Image Translation Networks
Ming-Yu Liu · Thomas Breuel · Jan Kautz
Poster
Dates n/a. @ None
A Screening Rule for l1-Regularized Ising Model Estimation
Zhaobin Kuang · Sinong Geng · David Page
Poster
Dates n/a. @ None
Geometric Descent Method for Convex Composite Minimization
Shixiang Chen · Shiqian Ma · Wei Liu
Poster
Dates n/a. @ None
Avoiding Discrimination through Causal Reasoning
Niki Kilbertus · Mateo Rojas Carulla · Giambattista Parascandolo · Moritz Hardt · Dominik Janzing · Bernhard Schölkopf
Poster
Dates n/a. @ None
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization
Tomoya Murata · Taiji Suzuki
Poster
Dates n/a. @ None
Convergence Analysis of Two-layer Neural Networks with ReLU Activation
Yuanzhi Li · Yang Yuan
Poster
Dates n/a. @ None
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks
Nanyang Ye · Zhanxing Zhu · Rafal Mantiuk
Poster
Dates n/a. @ None
Adversarial Surrogate Losses for Ordinal Regression
Rizal Fathony · Mohammad Ali Bashiri · Brian Ziebart
Poster
Dates n/a. @ None
Adversarial Invariant Feature Learning
Qizhe Xie · Zihang Dai · Yulun Du · Eduard Hovy · Graham Neubig
Poster
Dates n/a. @ None
Flat2Sphere: Learning Spherical Convolution for Fast Features from 360° Imagery
Yu-Chuan Su · Kristen Grauman
Poster
Dates n/a. @ None
Recycling for Fairness: Learning with Conditional Distribution Matching Constraints
Novi Quadrianto · Viktoriia Sharmanska
Poster
Dates n/a. @ None
3D Shape Reconstruction by Modeling 2.5D Sketch
Jiajun Wu · Yifan Wang · Tianfan Xue · XINGYUAN SUN · Bill Freeman · Josh Tenenbaum
Poster
Dates n/a. @ None
Learning with Average Top-k Loss
Yanbo Fan · Siwei Lyu · Yiming Ying · Baogang Hu
Poster
Dates n/a. @ None
Nonparametric Online Regression while Learning the Metric
Ilja Kuzborskij · Nicolò Cesa-Bianchi
Poster
Dates n/a. @ None
f-GANs in an Information Geometric Nutshell
Richard Nock · Zac Cranko · Aditya Menon · Lizhen Qu
Poster
Dates n/a. @ None
Mixture-Rank Matrix Approximation for Collaborative Filtering
Dongsheng Li · Chao Chen · Wei Liu · Tun Lu · Ning Gu · Stephen Chu
Poster
Dates n/a. @ None
Multimodal Image-to-Image Translation by Enforcing Bi-Cycle Consistency
Jun-Yan Zhu · Richard Zhang · Deepak Pathak · Trevor Darrell · Oliver Wang · Eli Shechtman · Alexei Efros
Poster
Dates n/a. @ None
Inference in Graphical Models via Semidefinite Programming Hierarchies
Murat Erdogdu · Yash Deshpande · Andrea Montanari
Poster
Dates n/a. @ None
Pose Guided Person Image Generation
Liqian Ma · Xu Jia · Qianru Sun · Bernt Schiele · Tinne Tuytelaars · Luc Van Gool
Poster
Dates n/a. @ None
Variable Importance Using Decision Trees
Arash A Amini · Seyed Jalil Kazemitabar · Adam Bloniarz · Ameet S Talwalkar
Poster
Dates n/a. @ None
Learning a Multi-View Stereo Machine
Abhishek Kar · Jitendra Malik · Christian Häne
Poster
Dates n/a. @ None
Universal Style Transfer via Feature Transforms
Yijun Li · Chen Fang · Jimei Yang · Zhaowen Wang · Xin Lu · Ming-Hsuan Yang
Poster
Dates n/a. @ None
MaskRNN: Instance Level Video Object Segmentation
Yuan-Ting Hu · Jia-Bin Huang · Alexander Schwing
Poster
Dates n/a. @ None
Towards Accurate Binary Convolutional Neural Network
Wei Pan · Xiaofan Lin · Cong Zhao
Poster
Dates n/a. @ None
k-Support and Ordered Weighted Sparsity for Overlapping Groups: Hardness and Algorithms
Cong Lim · Stephen Wright
Poster
Dates n/a. @ None
On Structured Prediction Theory with Calibrated Convex Surrogate Losses
Anton Osokin · Francis Bach · Simon Lacoste-Julien
Poster
Dates n/a. @ None
Inferring Generative Model Structure with Static Analysis
Paroma Varma · Bryan He · Payal Bajaj · Nishith Khandwala · Christopher Ré
Poster
Dates n/a. @ None
A Linear-Time Kernel Goodness-of-Fit Test
Wittawat Jitkrittum · Wenkai Xu · Zoltan Szabo · Kenji Fukumizu · Arthur Gretton
Poster
Dates n/a. @ None
Group Sparse Additive Machine
Hong Chen · Xiaoqian Wang · Heng Huang
Poster
Dates n/a. @ None
The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings
Krzysztof Choromanski · Mark Rowland · Adrian Weller
Poster
Dates n/a. @ None
Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning
El Mahdi El Mhamdi · Rachid Guerraoui · Hadrien Hendrikx · Alexandre Maurer
Poster
Dates n/a. @ None
Scene Physics Acquisition via Visual De-animation
Jiajun Wu · Erika Lu · Pushmeet Kohli · Bill Freeman · Josh Tenenbaum
Poster
Dates n/a. @ None
Scalable Generalized Linear Bandits: Online Computation and Hashing
Kwang-Sung Jun · Aniruddha Bhargava · Robert Nowak · Rebecca Willett
Poster
Dates n/a. @ None
Decoding with Value Networks for Neural Machine Translation
Di He · Hanqing Lu · Yingce Xia · Tao Qin · Liwei Wang · Tieyan Liu
Poster
Dates n/a. @ None
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models
Chris Oates · Steven Niederer · Angela Lee · François-Xavier Briol · Mark Girolami
Poster
Dates n/a. @ None
Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization
Fabian Pedregosa · Rémi Leblond · Simon Lacoste-Julien
Poster
Dates n/a. @ None
Dilated Recurrent Neural Networks
Shiyu Chang · Yang Zhang · Wei Han · Mo Yu · Xiaoxiao Guo · Wei Tan · Xiaodong Cui · Michael Witbrock · Mark A Hasegawa-Johnson · Thomas Huang
Poster
Dates n/a. @ None
Deep Subspace Clustering Network
Pan Ji · Tong Zhang · Hongdong Li · Mathieu Salzmann · Ian Reid
Poster
Dates n/a. @ None
On the Consistency of Quick Shift
Heinrich Jiang
Poster
Dates n/a. @ None
Concentration of Multilinear Functions of the Ising Model with Applications to Network Data
Constantinos Daskalakis · Nishanth Dikkala · Gautam Kamath
Poster
Dates n/a. @ None
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks
Zelun Luo · Yuliang Zou · Judy Hoffman · Fei Fei F Li
Poster
Dates n/a. @ None
Sharpness, Restart and Acceleration
Vincent Roulet · Alexandre d'Aspremont