Papers Accepted to ICLR 2020

Here is an interactive table of all ICLR 2020 papers.
Author

Seungjae Ryan Lee

Published

December 24, 2019

Here are all the papers accepted to ICLR 2020. For this post, I used the data collected by shaohua0116/ICLR2020-OpenReviewData.

For just reinforcement learning papers, check this post.

Rank Average Rating Title Ratings Variance Decision
1 8.00 Optimal Strategies Against Generative Attacks 8 8 8 8 0.00 Accept (Talk)
1 8.00 Sparse Coding With Gated Learned Ista 8 8 8 0.00 Accept (Spotlight)
1 8.00 Dynamics-aware Unsupervised Skill Discovery 8 8 8 0.00 Accept (Talk)
1 8.00 Cater: A Diagnostic Dataset For Compositional Actions & Temporal Reasoning 8 8 8 0.00 Accept (Talk)
1 8.00 Learning To Balance: Bayesian Meta-learning For Imbalanced And Out-of-distribution Tasks 8 8 8 0.00 Accept (Talk)
1 8.00 A Generalized Training Approach For Multiagent Learning 8 8 8 0.00 Accept (Talk)
1 8.00 Contrastive Learning Of Structured World Models 8 8 8 0.00 Accept (Talk)
1 8.00 Enhancing Adversarial Defense By K-winners-take-all 8 8 8 0.00 Accept (Spotlight)
1 8.00 Backpack: Packing More Into Backprop 8 8 8 0.00 Accept (Talk)
1 8.00 Principled Weight Initialization For Hypernetworks 8 8 8 0.00 Accept (Talk)
1 8.00 Understanding And Robustifying Differentiable Architecture Search 8 8 8 0.00 Accept (Talk)
1 8.00 Restricting The Flow: Information Bottlenecks For Attribution 8 8 8 0.00 Accept (Talk)
1 8.00 Implementation Matters In Deep Rl: A Case Study On Ppo And Trpo 8 8 8 0.00 Accept (Talk)
1 8.00 Nas-bench-102: Extending The Scope Of Reproducible Neural Architecture Search 8 8 8 0.00 Accept (Spotlight)
1 8.00 Mathematical Reasoning In Latent Space 8 8 8 0.00 Accept (Talk)
1 8.00 Mirror-generative Neural Machine Translation 8 8 8 0.00 Accept (Talk)
1 8.00 Rotation-invariant Clustering Of Functional Cell Types In Primary Visual Cortex 8 8 8 0.00 Accept (Talk)
1 8.00 On The “steerability” Of Generative Adversarial Networks 8 8 8 0.00 Accept (Poster)
1 8.00 The Logical Expressiveness Of Graph Neural Networks 8 8 8 0.00 Accept (Spotlight)
1 8.00 Meta-learning With Warped Gradient Descent 8 8 8 0.00 Accept (Talk)
1 8.00 Differentiable Reasoning Over A Virtual Knowledge Base 8 8 8 0.00 Accept (Talk)
1 8.00 Differentiation Of Blackbox Combinatorial Solvers 8 8 8 0.00 Accept (Spotlight)
1 8.00 Geometric Analysis Of Nonconvex Optimization Landscapes For Overcomplete Learning 8 8 8 0.00 Accept (Talk)
1 8.00 Simplified Action Decoder For Deep Multi-agent Reinforcement Learning 8 8 8 0.00 Accept (Spotlight)
1 8.00 Gendice: Generalized Offline Estimation Of Stationary Values 8 8 8 0.00 Accept (Talk)
1 8.00 Data-dependent Gaussian Prior Objective For Language Generation 8 8 8 0.00 Accept (Talk)
1 8.00 Causal Discovery With Reinforcement Learning 8 8 8 0.00 Accept (Talk)
1 8.00 How Much Position Information Do Convolutional Neural Networks Encode? 8 8 8 0.00 Accept (Spotlight)
1 8.00 Why Gradient Clipping Accelerates Training: A Theoretical Justification For Adaptivity 8 8 8 0.00 Accept (Talk)
1 8.00 A Theory Of Usable Information Under Computational Constraints 8 8 0.00 Accept (Talk)
1 8.00 Freelb: Enhanced Adversarial Training For Language Understanding 8 8 0.00 Accept (Spotlight)
1 8.00 Hyper-sagnn: A Self-attention Based Graph Neural Network For Hypergraphs 8 8 0.00 Accept (Poster)
1 8.00 Smooth Markets: A Basic Mechanism For Organizing Gradient-based Learners 8 8 0.00 Accept (Poster)
1 8.00 Depth-width Trade-offs For Relu Networks Via Sharkovsky’s Theorem 8 8 0.00 Accept (Spotlight)
2 7.50 Vq-wav2vec: Self-supervised Learning Of Discrete Speech Representations 8 6 8 8 0.75 Accept (Poster)
2 7.50 Rna Secondary Structure Prediction By Learning Unrolled Algorithms 8 8 8 6 0.75 Accept (Talk)
3 7.33 Is A Good Representation Sufficient For Sample Efficient Reinforcement Learning? 8 8 6 0.89 Accept (Spotlight)
3 7.33 Adversarial Training And Provable Defenses: Bridging The Gap 8 6 8 0.89 Accept (Talk)
3 7.33 Low-resource Knowledge-grounded Dialogue Generation 6 8 8 0.89 Accept (Poster)
3 7.33 Truth Or Backpropaganda? An Empirical Investigation Of Deep Learning Theory 8 6 8 0.89 Accept (Spotlight)
3 7.33 Directional Message Passing For Molecular Graphs 6 8 8 0.89 Accept (Spotlight)
3 7.33 Reformer: The Efficient Transformer 8 8 6 0.89 Accept (Talk)
3 7.33 Cross-lingual Alignment Vs Joint Training: A Comparative Study And A Simple Unified Framework 6 8 8 0.89 Accept (Poster)
3 7.33 What Graph Neural Networks Cannot Learn: Depth Vs Width 8 6 8 0.89 Accept (Poster)
3 7.33 Assemblenet: Searching For Multi-stream Neural Connectivity In Video Architectures 6 8 8 0.89 Accept (Poster)
3 7.33 Compressive Transformers For Long-range Sequence Modelling 6 8 8 0.89 Accept (Poster)
3 7.33 At Stability’s Edge: How To Adjust Hyperparameters To Preserve Minima Selection In Asynchronous Training Of Neural Networks? 8 6 8 0.89 Accept (Spotlight)
3 7.33 Comparing Fine-tuning And Rewinding In Neural Network Pruning 8 6 8 0.89 Accept (Talk)
3 7.33 Mogrifier Lstm 6 8 8 0.89 Accept (Talk)
3 7.33 Graphzoom: A Multi-level Spectral Approach For Accurate And Scalable Graph Embedding 8 8 6 0.89 Accept (Talk)
3 7.33 Reconstructing Continuous Distributions Of 3d Protein Structure From Cryo-em Images 6 8 8 0.89 Accept (Spotlight)
3 7.33 Neural Network Branching For Neural Network Verification 8 6 8 0.89 Accept (Talk)
3 7.33 Online And Stochastic Optimization Beyond Lipschitz Continuity: A Riemannian Approach 8 8 6 0.89 Accept (Spotlight)
3 7.33 Polylogarithmic Width Suffices For Gradient Descent To Achieve Arbitrarily Small Test Error With Shallow Relu Networks 8 6 8 0.89 Accept (Poster)
3 7.33 Deep Network Classification By Scattering And Homotopy Dictionary Learning 8 8 6 0.89 Accept (Poster)
3 7.33 Meta-learning Without Memorization 8 6 8 0.89 Accept (Spotlight)
3 7.33 Harnessing Structures For Value-based Planning And Reinforcement Learning 6 8 8 0.89 Accept (Talk)
3 7.33 Unbiased Contrastive Divergence Algorithm For Training Energy-based Latent Variable Models 6 8 8 0.89 Accept (Spotlight)
3 7.33 Explain Your Move: Understanding Agent Actions Using Focused Feature Saliency 6 8 8 0.89 Accept (Poster)
3 7.33 Disentangling Neural Mechanisms For Perceptual Grouping 6 8 8 0.89 Accept (Spotlight)
3 7.33 Mixed-curvature Variational Autoencoders 6 8 8 0.89 Accept (Poster)
3 7.33 Symplectic Ode-net: Learning Hamiltonian Dynamics With Control 6 8 8 0.89 Accept (Poster)
3 7.33 Deep Batch Active Learning By Diverse, Uncertain Gradient Lower Bounds 8 6 8 0.89 Accept (Talk)
3 7.33 Deep Imitative Models For Flexible Inference, Planning, And Control 8 6 8 0.89 Accept (Poster)
3 7.33 Cyclical Stochastic Gradient Mcmc For Bayesian Deep Learning 6 8 8 0.89 Accept (Talk)
3 7.33 Scaling Autoregressive Video Models 6 8 8 0.89 Accept (Spotlight)
3 7.33 Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps 8 8 6 0.89 Accept (Spotlight)
3 7.33 A Mutual Information Maximization Perspective Of Language Representation Learning 6 8 8 0.89 Accept (Spotlight)
3 7.33 Ddsp: Differentiable Digital Signal Processing 8 6 8 0.89 Accept (Spotlight)
3 7.33 On Mutual Information Maximization For Representation Learning 8 8 6 0.89 Accept (Poster)
3 7.33 Observational Overfitting In Reinforcement Learning 6 8 8 0.89 Accept (Poster)
3 7.33 Federated Learning With Matched Averaging 6 8 8 0.89 Accept (Talk)
3 7.33 Latent Normalizing Flows For Many-to-many Cross Domain Mappings 6 8 8 0.89 Accept (Poster)
3 7.33 Convolutional Conditional Neural Processes 6 8 8 0.89 Accept (Talk)
3 7.33 Meta-q-learning 8 8 6 0.89 Accept (Talk)
3 7.33 Measuring The Reliability Of Reinforcement Learning Algorithms 8 8 6 0.89 Accept (Spotlight)
3 7.33 Physics-aware Difference Graph Networks For Sparsely-observed Dynamics 8 8 6 0.89 Accept (Poster)
3 7.33 Learning Hierarchical Discrete Linguistic Units From Visually-grounded Speech 6 8 8 0.89 Accept (Talk)
3 7.33 Symplectic Recurrent Neural Networks 8 8 6 0.89 Accept (Spotlight)
3 7.33 End To End Trainable Active Contours Via Differentiable Rendering 8 8 6 0.89 Accept (Poster)
3 7.33 What Can Neural Networks Reason About? 8 6 8 0.89 Accept (Spotlight)
3 7.33 Discriminative Particle Filter Reinforcement Learning For Complex Partial Observations 8 6 8 0.89 Accept (Poster)
3 7.33 Thieves On Sesame Street! Model Extraction Of Bert-based Apis 6 8 8 0.89 Accept (Poster)
3 7.33 High Fidelity Speech Synthesis With Adversarial Networks 8 6 8 0.89 Accept (Talk)
3 7.33 Disagreement-regularized Imitation Learning 6 8 8 0.89 Accept (Spotlight)
3 7.33 Stable Rank Normalization For Improved Generalization In Neural Networks And Gans 6 8 8 0.89 Accept (Spotlight)
3 7.33 Doubly Robust Bias Reduction In Infinite Horizon Off-policy Estimation 6 8 8 0.89 Accept (Spotlight)
3 7.33 Fasterseg: Searching For Faster Real-time Semantic Segmentation 6 8 8 0.89 Accept (Poster)
3 7.33 Robust Subspace Recovery Layer For Unsupervised Anomaly Detection 6 8 8 0.89 Accept (Poster)
3 7.33 Seed Rl: Scalable And Efficient Deep-rl With Accelerated Central Inference 8 6 8 0.89 Accept (Talk)
3 7.33 On The Equivalence Between Node Embeddings And Structural Graph Representations 6 8 8 0.89 Accept (Poster)
3 7.33 Harnessing The Power Of Infinitely Wide Deep Nets On Small-data Tasks 8 6 8 0.89 Accept (Spotlight)
3 7.33 The Ingredients Of Real World Robotic Reinforcement Learning 6 8 8 0.89 Accept (Spotlight)
3 7.33 Watch The Unobserved: A Simple Approach To Parallelizing Monte Carlo Tree Search 8 6 8 0.89 Accept (Talk)
3 7.33 Meta-learning Acquisition Functions For Transfer Learning In Bayesian Optimization 8 6 8 0.89 Accept (Spotlight)
3 7.33 On The Convergence Of Fedavg On Non-iid Data 6 8 8 0.89 Accept (Talk)
3 7.33 Classification-based Anomaly Detection For General Data 8 8 6 0.89 Accept (Poster)
3 7.33 Learning Robust Representations Via Multi-view Information Bottleneck 6 8 8 0.89 Accept (Poster)
3 7.33 Poly-encoders: Architectures And Pre-training Strategies For Fast And Accurate Multi-sentence Scoring 8 6 8 0.89 Accept (Poster)
3 7.33 Your Classifier Is Secretly An Energy Based Model And You Should Treat It Like One 6 8 8 0.89 Accept (Talk)
3 7.33 Deep Learning For Symbolic Mathematics 8 8 6 0.89 Accept (Spotlight)
3 7.33 Progressive Learning And Disentanglement Of Hierarchical Representations 6 8 8 0.89 Accept (Spotlight)
3 7.33 Energy-based Models For Atomic-resolution Protein Conformations 6 8 8 0.89 Accept (Spotlight)
3 7.33 Lambdanet: Probabilistic Type Inference Using Graph Neural Networks 6 8 8 0.89 Accept (Poster)
3 7.33 Sumo: Unbiased Estimation Of Log Marginal Probability For Latent Variable Models 6 8 8 0.89 Accept (Spotlight)
3 7.33 Glad: Learning Sparse Graph Recovery 8 6 8 0.89 Accept (Poster)
3 7.33 Program Guided Agent 8 6 8 0.89 Accept (Spotlight)
3 7.33 Graph Neural Networks Exponentially Lose Expressive Power For Node Classification 8 6 8 0.89 Accept (Spotlight)
3 7.33 A Closer Look At Deep Policy Gradients 8 6 8 0.89 Accept (Talk)
3 7.33 Fast Task Inference With Variational Intrinsic Successor Features 8 6 8 0.89 Accept (Talk)
3 7.33 Generalization Of Two-layer Neural Networks: An Asymptotic Viewpoint 8 6 8 0.89 Accept (Spotlight)
3 7.33 Electra: Pre-training Text Encoders As Discriminators Rather Than Generators 8 8 6 0.89 Accept (Poster)
3 7.33 Network Deconvolution 6 8 8 0.89 Accept (Spotlight)
3 7.33 Intensity-free Learning Of Temporal Point Processes 8 6 8 0.89 Accept (Spotlight)
3 7.33 Fspool: Learning Set Representations With Featurewise Sort Pooling 8 8 6 0.89 Accept (Poster)
3 7.33 Massively Multilingual Sparse Word Representations 6 8 8 0.89 Accept (Poster)
3 7.33 Finite Depth And Width Corrections To The Neural Tangent Kernel 6 8 8 0.89 Accept (Spotlight)
3 7.33 Gradient Descent Maximizes The Margin Of Homogeneous Neural Networks 8 8 6 0.89 Accept (Talk)
3 7.33 Sequential Latent Knowledge Selection For Knowledge-grounded Dialogue 8 8 6 0.89 Accept (Spotlight)
3 7.33 Learning To Plan In High Dimensions Via Neural Exploration-exploitation Trees 8 8 6 0.89 Accept (Spotlight)
3 7.33 Albert: A Lite Bert For Self-supervised Learning Of Language Representations 8 8 6 0.89 Accept (Spotlight)
4 7.00 An Exponential Learning Rate Schedule For Batch Normalized Networks 8 8 6 6 1.00 Accept (Spotlight)
4 7.00 Encoding Word Order In Complex Embeddings 8 6 8 6 1.00 Accept (Spotlight)
4 7.00 And The Bit Goes Down: Revisiting The Quantization Of Neural Networks 8 6 8 6 1.00 Accept (Spotlight)
4 7.00 Quantum Algorithms For Deep Convolutional Neural Networks 6 8 8 6 1.00 Accept (Poster)
4 7.00 Target-embedding Autoencoders For Supervised Representation Learning 6 8 6 8 1.00 Accept (Talk)
4 7.00 Dream To Control: Learning Behaviors By Latent Imagination 8 6 6 8 1.00 Accept (Spotlight)
4 7.00 Memo: A Deep Network For Flexible Combination Of Episodic Memories 6 8 1.00 Accept (Poster)
4 7.00 Explanation By Progressive Exaggeration 6 8 1.00 Accept (Spotlight)
4 7.00 Ridge Regression: Structure, Cross-validation, And Sketching 6 8 1.00 Accept (Spotlight)
4 7.00 Double Neural Counterfactual Regret Minimization 8 6 1.00 Accept (Poster)
4 7.00 Biologically Inspired Sleep Algorithm For Increased Generalization And Adversarial Robustness In Deep Neural Networks 6 8 1.00 Accept (Poster)
4 7.00 Spectral Embedding Of Regularized Block Models 8 6 1.00 Accept (Spotlight)
4 7.00 How The Choice Of Activation Affects Training Of Overparametrized Neural Nets 6 8 1.00 Accept (Poster)
4 7.00 Understanding L4-based Dictionary Learning: Interpretation, Stability, And Robustness 8 6 1.00 Accept (Poster)
4 7.00 Neural Tangent Kernels, Transportation Mappings, And Universal Approximation 8 6 1.00 Accept (Poster)
4 7.00 Sliced Cramer Synaptic Consolidation For Preserving Deeply Learned Representations 6 8 1.00 Accept (Spotlight)
4 7.00 Language Gans Falling Short 6 8 1.00 Accept (Poster)
4 7.00 Building Deep Equivariant Capsule Networks 8 6 1.00 Accept (Talk)
5 6.75 An Inductive Bias For Distances: Neural Nets That Respect The Triangle Inequality 8 8 3 8 4.69 Accept (Poster)
6 6.67 Disentanglement Through Nonlinear Ica With General Incompressible-flow Networks (gin) 8 6 6 0.89 Accept (Spotlight)
6 6.67 Fooling Detection Alone Is Not Enough: Adversarial Attack Against Multiple Object Tracking 8 6 6 0.89 Accept (Poster)
6 6.67 In Search For A Sat-friendly Binarized Neural Network Architecture 8 6 6 0.89 Accept (Poster)
6 6.67 Dba: Distributed Backdoor Attacks Against Federated Learning 6 8 6 0.89 Accept (Poster)
6 6.67 Genesis: Generative Scene Inference And Sampling With Object-centric Latent Representations 6 6 8 0.89 Accept (Poster)
6 6.67 Measuring Compositional Generalization: A Comprehensive Method On Realistic Data 6 8 6 0.89 Accept (Poster)
6 6.67 Lagrangian Fluid Simulation With Continuous Convolutions 6 8 6 0.89 Accept (Poster)
6 6.67 Making Efficient Use Of Demonstrations To Solve Hard Exploration Problems 6 8 6 0.89 Accept (Poster)
6 6.67 Intrinsic Motivation For Encouraging Synergistic Behavior 6 8 6 0.89 Accept (Poster)
6 6.67 On Robustness Of Neural Ordinary Differential Equations 6 8 6 0.89 Accept (Spotlight)
6 6.67 On Identifiability In Transformers 6 8 6 0.89 Accept (Poster)
6 6.67 Estimating Gradients For Discrete Random Variables By Sampling Without Replacement 6 6 8 0.89 Accept (Spotlight)
6 6.67 Gradient-based Neural Dag Learning 6 6 8 0.89 Accept (Poster)
6 6.67 Incremental Rnn: A Dynamical View. 8 6 6 0.89 Accept (Poster)
6 6.67 Deep Double Descent: Where Bigger Models And More Data Hurt 8 6 6 0.89 Accept (Poster)
6 6.67 Learning To Retrieve Reasoning Paths Over Wikipedia Graph For Question Answering 6 6 8 0.89 Accept (Poster)
6 6.67 Simple And Effective Regularization Methods For Training On Noisily Labeled Data With Generalization Guarantee 6 8 6 0.89 Accept (Poster)
6 6.67 Sqil: Imitation Learning Via Reinforcement Learning With Sparse Rewards 8 6 6 0.89 Accept (Poster)
6 6.67 Reinforcement Learning With Competitive Ensembles Of Information-constrained Primitives 8 6 6 0.89 Accept (Poster)
6 6.67 Neural Outlier Rejection For Self-supervised Keypoint Learning 6 6 8 0.89 Accept (Poster)
6 6.67 Rényi Fair Inference 6 6 8 0.89 Accept (Poster)
6 6.67 U-gat-it: Unsupervised Generative Attentional Networks With Adaptive Layer-instance Normalization For Image-to-image Translation 6 8 6 0.89 Accept (Poster)
6 6.67 Multi-agent Interactions Modeling With Correlated Policies 6 6 8 0.89 Accept (Poster)
6 6.67 Decoupling Representation And Classifier For Long-tailed Recognition 6 8 6 0.89 Accept (Poster)
6 6.67 Estimating Counterfactual Treatment Outcomes Over Time Through Adversarially Balanced Representations 8 6 6 0.89 Accept (Spotlight)
6 6.67 Neural Symbolic Reader: Scalable Integration Of Distributed And Symbolic Representations For Reading Comprehension 6 6 8 0.89 Accept (Spotlight)
6 6.67 Inductive Representation Learning On Temporal Graphs 6 6 8 0.89 Accept (Poster)
6 6.67 Training Generative Adversarial Networks From Incomplete Observations Using Factorised Discriminators 6 8 6 0.89 Accept (Poster)
6 6.67 Denoising And Regularization Via Exploiting The Structural Bias Of Convolutional Generators 6 8 6 0.89 Accept (Poster)
6 6.67 Controlling Generative Models With Continuous Factors Of Variations 6 8 6 0.89 Accept (Poster)
6 6.67 Intrinsically Motivated Discovery Of Diverse Patterns In Self-organizing Systems 6 6 8 0.89 Accept (Talk)
6 6.67 Influence-based Multi-agent Exploration 6 6 8 0.89 Accept (Spotlight)
6 6.67 Asymptotics Of Wide Networks From Feynman Diagrams 8 6 6 0.89 Accept (Spotlight)
6 6.67 Provable Robustness Against All Adversarial -perturbations For 6 8 6 0.89 Accept (Poster)
6 6.67 From Variational To Deterministic Autoencoders 6 8 6 0.89 Accept (Poster)
6 6.67 A Probabilistic Formulation Of Unsupervised Text Style Transfer 8 6 6 0.89 Accept (Spotlight)
6 6.67 Black-box Adversarial Attack With Transferable Model-based Embedding 6 8 6 0.89 Accept (Poster)
6 6.67 Discrepancy Ratio: Evaluating Model Performance When Even Experts Disagree On The Truth 6 6 8 0.89 Accept (Poster)
6 6.67 Pitfalls Of In-domain Uncertainty Estimation And Ensembling In Deep Learning 6 6 8 0.89 Accept (Poster)
6 6.67 Learning The Arrow Of Time For Problems In Reinforcement Learning 6 6 8 0.89 Accept (Poster)
6 6.67 Transformer-xh: Multi-hop Question Answering With Extra Hop Attention 6 8 6 0.89 Accept (Poster)
6 6.67 Learned Step Size Quantization 6 6 8 0.89 Accept (Poster)
6 6.67 Mutual Mean-teaching: Pseudo Label Refinery For Unsupervised Domain Adaptation On Person Re-identification 6 8 6 0.89 Accept (Poster)
6 6.67 Ensemble Distribution Distillation 6 6 8 0.89 Accept (Poster)
6 6.67 Drawing Early-bird Tickets: Toward More Efficient Training Of Deep Networks 8 6 6 0.89 Accept (Spotlight)
6 6.67 Detecting And Diagnosing Adversarial Images With Class-conditional Capsule Reconstructions 6 8 6 0.89 Accept (Poster)
6 6.67 Order Learning And Its Application To Age Estimation 6 6 8 0.89 Accept (Poster)
6 6.67 Inductive Matrix Completion Based On Graph Neural Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Posterior Sampling For Multi-agent Reinforcement Learning: Solving Extensive Games With Imperfect Information 6 6 8 0.89 Accept (Talk)
6 6.67 Intriguing Properties Of Adversarial Training At Scale 6 8 6 0.89 Accept (Poster)
6 6.67 Efficient Transformer For Mobile Applications 6 8 6 0.89 Accept (Poster)
6 6.67 Reducing Transformer Depth On Demand With Structured Dropout 6 6 8 0.89 Accept (Poster)
6 6.67 A Theoretical Analysis Of The Number Of Shots In Few-shot Learning 8 6 6 0.89 Accept (Poster)
6 6.67 Learning Representations For Binary-classification Without Backpropagation 8 6 6 0.89 Accept (Poster)
6 6.67 Fsnet: Compression Of Deep Convolutional Neural Networks By Filter Summary 8 6 6 0.89 Accept (Poster)
6 6.67 Amrl: Aggregated Memory For Reinforcement Learning 6 6 8 0.89 Accept (Poster)
6 6.67 The Function Of Contextual Illusions 6 6 8 0.89 Accept (Poster)
6 6.67 Neural Machine Translation With Universal Visual Representation 6 8 6 0.89 Accept (Spotlight)
6 6.67 Information Geometry Of Orthogonal Initializations And Training 6 8 6 0.89 Accept (Poster)
6 6.67 Batch-shaping For Learning Conditional Channel Gated Networks 6 6 8 0.89 Accept (Poster)
6 6.67 Multi-scale Representation Learning For Spatial Feature Distributions Using Grid Cells 6 8 6 0.89 Accept (Spotlight)
6 6.67 Query-efficient Meta Attack To Deep Neural Networks 6 8 6 0.89 Accept (Poster)
6 6.67 A Fair Comparison Of Graph Neural Networks For Graph Classification 6 8 6 0.89 Accept (Poster)
6 6.67 Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates 6 8 6 0.89 Accept (Poster)
6 6.67 Monotonic Multihead Attention 6 8 6 0.89 Accept (Poster)
6 6.67 Continual Learning With Hypernetworks 6 8 6 0.89 Accept (Poster)
6 6.67 Decoding As Dynamic Programming For Recurrent Autoregressive Models 6 6 8 0.89 Accept (Poster)
6 6.67 Diverse Trajectory Forecasting With Determinantal Point Processes 8 6 6 0.89 Accept (Poster)
6 6.67 Co-attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-occurring In Data 6 8 6 0.89 Accept (Poster)
6 6.67 Multiplicative Interactions And Where To Find Them 6 8 6 0.89 Accept (Poster)
6 6.67 You Can Teach An Old Dog New Tricks! On Training Knowledge Graph Embeddings 8 6 6 0.89 Accept (Poster)
6 6.67 Deepsphere: A Graph-based Spherical Cnn 8 6 6 0.89 Accept (Spotlight)
6 6.67 Learning To Control Pdes With Differentiable Physics 6 8 6 0.89 Accept (Spotlight)
6 6.67 Emergence Of Functional And Structural Properties Of The Head Direction System By Optimization Of Recurrent Neural Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Model Based Reinforcement Learning For Atari 6 8 6 0.89 Accept (Spotlight)
6 6.67 Dynamically Pruned Message Passing Networks For Large-scale Knowledge Graph Reasoning 6 8 6 0.89 Accept (Poster)
6 6.67 Mixout: Effective Regularization To Finetune Large-scale Pretrained Language Models 6 8 6 0.89 Accept (Poster)
6 6.67 On The Geometry And Learning Low-dimensional Embeddings For Directed Graphs 6 6 8 0.89 Accept (Poster)
6 6.67 The Break-even Point On The Optimization Trajectories Of Deep Neural Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Understanding And Improving Information Transfer In Multi-task Learning 8 6 6 0.89 Accept (Poster)
6 6.67 Abductive Commonsense Reasoning 6 8 6 0.89 Accept (Poster)
6 6.67 Tree-structured Attention With Hierarchical Accumulation 6 6 8 0.89 Accept (Poster)
6 6.67 Pay Attention To Features, Transfer Learn Faster Cnns 8 6 6 0.89 Accept (Poster)
6 6.67 Gradientless Descent: High-dimensional Zeroth-order Optimization 6 8 6 0.89 Accept (Spotlight)
6 6.67 Knowledge Consistency Between Neural Networks And Beyond 6 8 6 0.89 Accept (Poster)
6 6.67 Learning From Rules Generalizing Labeled Exemplars 6 8 6 0.89 Accept (Spotlight)
6 6.67 Variational Recurrent Models For Solving Partially Observable Control Tasks 6 6 8 0.89 Accept (Poster)
6 6.67 Towards Hierarchical Importance Attribution: Explaining Compositional Semantics For Neural Sequence Models 6 6 8 0.89 Accept (Spotlight)
6 6.67 Tranquil Clouds: Neural Networks For Learning Temporally Coherent Features In Point Clouds 6 8 6 0.89 Accept (Spotlight)
6 6.67 Spike-based Causal Inference For Weight Alignment 8 6 6 0.89 Accept (Poster)
6 6.67 Sample Efficient Policy Gradient Methods With Recursive Variance Reduction 6 8 6 0.89 Accept (Poster)
6 6.67 Exploring Model-based Planning With Policy Networks 6 8 6 0.89 Accept (Poster)
6 6.67 Variational Autoencoders For Highly Multivariate Spatial Point Processes Intensities 6 8 6 0.89 Accept (Poster)
6 6.67 Kernelized Wasserstein Natural Gradient 6 8 6 0.89 Accept (Spotlight)
6 6.67 Can Gradient Clipping Mitigate Label Noise? 6 6 8 0.89 Accept (Poster)
6 6.67 Rethinking The Security Of Skip Connections In Resnet-like Neural Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Reinforcement Learning Based Graph-to-sequence Model For Natural Question Generation 6 6 8 0.89 Accept (Poster)
6 6.67 Deep Neuroethology Of A Virtual Rodent 6 6 8 0.89 Accept (Spotlight)
6 6.67 Pretrained Encyclopedia: Weakly Supervised Knowledge-pretrained Language Model 6 6 8 0.89 Accept (Poster)
6 6.67 N-beats: Neural Basis Expansion Analysis For Interpretable Time Series Forecasting 6 6 8 0.89 Accept (Poster)
6 6.67 Uncertainty-guided Continual Learning With Bayesian Neural Networks 8 6 6 0.89 Accept (Poster)
6 6.67 Toward Amortized Ranking-critical Training For Collaborative Filtering 6 6 8 0.89 Accept (Poster)
6 6.67 Revisiting Self-training For Neural Sequence Generation 6 6 8 0.89 Accept (Poster)
6 6.67 A Neural Dirichlet Process Mixture Model For Task-free Continual Learning 8 6 6 0.89 Accept (Poster)
6 6.67 Ride: Rewarding Impact-driven Exploration For Procedurally-generated Environments 6 6 8 0.89 Accept (Poster)
6 6.67 Neurquri: Neural Question Requirement Inspector For Answerability Prediction In Machine Reading Comprehension 6 6 8 0.89 Accept (Poster)
6 6.67 Actor-critic Provably Finds Nash Equilibria Of Linear-quadratic Mean-field Games 6 6 8 0.89 Accept (Poster)
6 6.67 Lipschitz Constant Estimation For Neural Networks Via Sparse Polynomial Optimization 6 8 6 0.89 Accept (Poster)
6 6.67 A Latent Morphology Model For Open-vocabulary Neural Machine Translation 8 6 6 0.89 Accept (Spotlight)
6 6.67 Are Pre-trained Language Models Aware Of Phrases? Simple But Strong Baselines For Grammar Induction 6 6 8 0.89 Accept (Poster)
6 6.67 Padé Activation Units: End-to-end Learning Of Flexible Activation Functions In Deep Networks 6 8 6 0.89 Accept (Poster)
6 6.67 Improving Adversarial Robustness Requires Revisiting Misclassified Examples 8 6 6 0.89 Accept (Poster)
6 6.67 Learning Expensive Coordination: An Event-based Deep Rl Approach 6 8 6 0.89 Accept (Poster)
6 6.67 Scalable Model Compression By Entropy Penalized Reparameterization 6 8 6 0.89 Accept (Poster)
6 6.67 Permutation Equivariant Models For Compositional Generalization In Language 8 6 6 0.89 Accept (Poster)
6 6.67 Evolutionary Population Curriculum For Scaling Multi-agent Reinforcement Learning 6 8 6 0.89 Accept (Poster)
6 6.67 On The Interaction Between Supervision And Self-play In Emergent Communication 6 8 6 0.89 Accept (Poster)
6 6.67 Locality And Compositionality In Zero-shot Learning 8 6 6 0.89 Accept (Poster)
6 6.67 Distributed Bandit Learning: Near-optimal Regret With Efficient Communication 8 6 6 0.89 Accept (Poster)
6 6.67 Fast Is Better Than Free: Revisiting Adversarial Training 8 6 6 0.89 Accept (Poster)
6 6.67 Towards Stabilizing Batch Statistics In Backward Propagation Of Batch Normalization 6 8 6 0.89 Accept (Poster)
6 6.67 Extreme Tensoring For Low-memory Preconditioning 8 6 6 0.89 Accept (Poster)
6 6.67 Scale-equivariant Steerable Networks 6 6 8 0.89 Accept (Poster)
6 6.67 Query2box: Reasoning Over Knowledge Graphs In Vector Space Using Box Embeddings 6 6 8 0.89 Accept (Poster)
6 6.67 Consistency Regularization For Generative Adversarial Networks 8 6 6 0.89 Accept (Poster)
6 6.67 Making Sense Of Reinforcement Learning And Probabilistic Inference 6 6 8 0.89 Accept (Spotlight)
6 6.67 Reclor: A Reading Comprehension Dataset Requiring Logical Reasoning 6 6 8 0.89 Accept (Poster)
6 6.67 Semi-supervised Generative Modeling For Controllable Speech Synthesis 6 8 6 0.89 Accept (Poster)
6 6.67 Reinforced Genetic Algorithm Learning For Optimizing Computation Graphs 8 6 6 0.89 Accept (Poster)
6 6.67 The Intriguing Role Of Module Criticality In The Generalization Of Deep Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Training Individually Fair Ml Models With Sensitive Subspace Robustness 8 6 6 0.89 Accept (Spotlight)
6 6.67 Tabfact: A Large-scale Dataset For Table-based Fact Verification 8 6 6 0.89 Accept (Poster)
6 6.67 Snode: Spectral Discretization Of Neural Odes For System Identification 6 6 8 0.89 Accept (Poster)
6 6.67 Clevrer: Collision Events For Video Representation And Reasoning 6 8 6 0.89 Accept (Spotlight)
6 6.67 Never Give Up: Learning Directed Exploration Strategies 6 6 8 0.89 Accept (Poster)
6 6.67 Robust Reinforcement Learning For Continuous Control With Model Misspecification 6 6 8 0.89 Accept (Poster)
6 6.67 Neural Module Networks For Reasoning Over Text 6 8 6 0.89 Accept (Poster)
6 6.67 Sign Bits Are All You Need For Black-box Attacks 8 6 6 0.89 Accept (Poster)
6 6.67 Learning To Learn By Zeroth-order Oracle 6 8 6 0.89 Accept (Poster)
6 6.67 Synthesizing Programmatic Policies That Inductively Generalize 6 8 6 0.89 Accept (Poster)
6 6.67 Hamiltonian Generative Networks 8 6 6 0.89 Accept (Spotlight)
6 6.67 Prediction, Consistency, Curvature: Representation Learning For Locally-linear Control 6 8 6 0.89 Accept (Poster)
6 6.67 A Function Space View Of Bounded Norm Infinite Width Relu Nets: The Multivariate Case 6 6 8 0.89 Accept (Poster)
6 6.67 Hilloc: Lossless Image Compression With Hierarchical Latent Variable Models 6 6 8 0.89 Accept (Poster)
6 6.67 Geom-gcn: Geometric Graph Convolutional Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Adaptive Correlated Monte Carlo For Contextual Categorical Sequence Generation 6 6 8 0.89 Accept (Poster)
6 6.67 Pc-darts: Partial Channel Connections For Memory-efficient Architecture Search 6 6 8 0.89 Accept (Spotlight)
6 6.67 Improving Generalization In Meta Reinforcement Learning Using Neural Objectives 6 6 8 0.89 Accept (Spotlight)
6 6.67 Compression Based Bound For Non-compressed Network: Unified Generalization Error Analysis Of Large Compressible Deep Neural Network 6 8 6 0.89 Accept (Spotlight)
6 6.67 Hoppity: Learning Graph Transformations To Detect And Fix Bugs In Programs 6 8 6 0.89 Accept (Spotlight)
6 6.67 Real Or Not Real, That Is The Question 8 6 6 0.89 Accept (Spotlight)
7 6.50 A Closer Look At The Approximation Capabilities Of Neural Networks 8 6 6 6 0.75 Accept (Poster)
7 6.50 Quantifying Point-prediction Uncertainty In Neural Networks Via Residual Estimation With An I/o Kernel 6 6 8 6 0.75 Accept (Poster)
7 6.50 Learning Compositional Koopman Operators For Model-based Control 6 6 6 8 0.75 Accept (Spotlight)
7 6.50 Learning To Guide Random Search 8 6 6 6 0.75 Accept (Poster)
7 6.50 Dynamic Time Lag Regression: Predicting What & When 8 6 6 6 0.75 Accept (Poster)
7 6.50 Deepv2d: Video To Depth With Differentiable Structure From Motion 6 6 6 8 0.75 Accept (Poster)
7 6.50 Rethinking Softmax Cross-entropy Loss For Adversarial Robustness 8 6 6 6 0.75 Accept (Poster)
8 6.33 Understanding Knowledge Distillation In Non-autoregressive Machine Translation 8 3 8 5.56 Accept (Poster)
8 6.33 Self-labelling Via Simultaneous Clustering And Representation Learning 8 3 8 5.56 Accept (Spotlight)
8 6.33 Self-adversarial Learning With Comparative Discrimination For Text Generation 3 8 8 5.56 Accept (Poster)
8 6.33 Defending Against Physically Realizable Attacks On Image Classification 3 8 8 5.56 Accept (Spotlight)
8 6.33 Lazy-cfr: Fast And Near-optimal Regret Minimization For Extensive Games With Imperfect Information 3 8 8 5.56 Accept (Poster)
8 6.33 Variational Template Machine For Data-to-text Generation 8 3 8 5.56 Accept (Poster)
8 6.33 Word2ket: Space-efficient Word Embeddings Inspired By Quantum Entanglement 3 8 8 5.56 Accept (Spotlight)
8 6.33 Rapid Learning Or Feature Reuse? Towards Understanding The Effectiveness Of Maml 8 3 8 5.56 Accept (Poster)
8 6.33 Learning Disentangled Representations For Counterfactual Regression 8 8 3 5.56 Accept (Poster)
8 6.33 Accelerating Sgd With Momentum For Over-parameterized Learning 8 8 3 5.56 Accept (Poster)
8 6.33 A Meta-transfer Objective For Learning To Disentangle Causal Mechanisms 3 8 8 5.56 Accept (Poster)
8 6.33 Learning From Explanations With Neural Module Execution Tree 3 8 8 5.56 Accept (Poster)
8 6.33 Fantastic Generalization Measures And Where To Find Them 8 3 8 5.56 Accept (Poster)
8 6.33 Guiding Program Synthesis By Learning To Generate Examples 8 3 8 5.56 Accept (Poster)
8 6.33 Single Episode Transfer For Differing Environmental Dynamics In Reinforcement Learning 3 8 8 5.56 Accept (Poster)
8 6.33 Triple Wins: Boosting Accuracy, Robustness And Efficiency Together By Enabling Input-adaptive Inference 3 8 8 5.56 Accept (Poster)
8 6.33 Coherent Gradients: An Approach To Understanding Generalization In Gradient Descent-based Optimization 8 8 3 5.56 Accept (Poster)
8 6.33 Learning-augmented Data Stream Algorithms 3 8 8 5.56 Accept (Poster)
8 6.33 Weakly Supervised Disentanglement With Guarantees 8 8 3 5.56 Accept (Poster)
8 6.33 Transferable Perturbations Of Deep Feature Distributions 8 3 8 5.56 Accept (Poster)
8 6.33 Measuring And Improving The Use Of Graph Information In Graph Neural Networks 8 3 8 5.56 Accept (Poster)
8 6.33 Automated Relational Meta-learning 3 8 8 5.56 Accept (Poster)
8 6.33 Minimizing Flops To Learn Efficient Sparse Representations 8 3 8 5.56 Accept (Poster)
8 6.33 Snow: Subscribing To Knowledge Via Channel Pooling For Transfer & Lifelong Learning 8 8 3 5.56 Accept (Poster)
8 6.33 Decentralized Distributed Ppo: Mastering Pointgoal Navigation 3 8 8 5.56 Accept (Poster)
8 6.33 Augmix: A Simple Data Processing Method To Improve Robustness And Uncertainty 8 3 8 5.56 Accept (Poster)
8 6.33 Counterfactuals Uncover The Modular Structure Of Deep Generative Models 8 3 8 5.56 Accept (Poster)
9 6.25 Improved Sample Complexities For Deep Neural Networks And Robust Classification Via An All-layer Margin 6 8 8 3 4.19 Accept (Poster)
9 6.25 Geometric Insights Into The Convergence Of Nonlinear Td Learning 8 3 6 8 4.19 Accept (Poster)
9 6.25 Dynamics-aware Embeddings 3 8 6 8 4.19 Accept (Poster)
10 6.20 Reanalysis Of Variance Reduced Temporal Difference Learning 8 8 6 3 6 3.36 Accept (Poster)
11 6.00 Meta-learning Deep Energy-based Memory Models 6 6 6 6 0.00 Accept (Poster)
11 6.00 Memory-based Graph Networks 6 6 6 6 0.00 Accept (Poster)
11 6.00 Training Binary Neural Networks With Real-to-binary Convolutions 6 6 6 6 0.00 Accept (Poster)
11 6.00 Lookahead: A Far-sighted Alternative Of Magnitude-based Pruning 6 6 6 6 0.00 Accept (Poster)
11 6.00 Q-learning With Ucb Exploration Is Sample Efficient For Infinite-horizon Mdp 6 6 6 6 0.00 Accept (Poster)
11 6.00 On The Variance Of The Adaptive Learning Rate And Beyond 6 6 6 0.00 Accept (Poster)
11 6.00 Emergent Systematic Generalization In A Situated Agent 6 6 6 0.00 Accept (Poster)
11 6.00 Quantifying The Cost Of Reliable Photo Authentication Via High-performance Learned Lossy Representations 6 6 6 0.00 Accept (Poster)
11 6.00 Automated Curriculum Generation Through Setter-solver Interactions 6 6 6 0.00 Accept (Poster)
11 6.00 Optimistic Exploration Even With A Pessimistic Initialisation 6 6 6 0.00 Accept (Poster)
11 6.00 Multi-agent Reinforcement Learning For Networked System Control 6 6 6 0.00 Accept (Poster)
11 6.00 Physics-as-inverse-graphics: Unsupervised Physical Parameter Estimation From Video 6 6 6 0.00 Accept (Poster)
11 6.00 On Solving Minimax Optimization Locally: A Follow-the-ridge Approach 6 6 6 0.00 Accept (Poster)
11 6.00 A Learning-based Iterative Method For Solving Vehicle Routing Problems 6 6 6 0.00 Accept (Poster)
11 6.00 Deephoyer: Learning Sparser Neural Network With Differentiable Scale-invariant Sparsity Measures 6 6 6 0.00 Accept (Poster)
11 6.00 Probabilistic Connection Importance Inference And Lossless Compression Of Deep Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Precision Gating: Improving Neural Network Efficiency With Dynamic Dual-precision Activations 6 6 6 0.00 Accept (Poster)
11 6.00 Learning To Link 6 6 6 0.00 Accept (Poster)
11 6.00 Remixmatch: Semi-supervised Learning With Distribution Matching And Augmentation Anchoring 6 6 6 0.00 Accept (Poster)
11 6.00 Differentially Private Meta-learning 6 6 6 0.00 Accept (Poster)
11 6.00 Fast Neural Network Adaptation Via Parameters Remapping 6 6 6 0.00 Accept (Poster)
11 6.00 Sharing Knowledge In Multi-task Deep Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Rtfm: Generalising To New Environment Dynamics Via Reading 6 6 6 0.00 Accept (Poster)
11 6.00 Strategies For Pre-training Graph Neural Networks 6 6 6 0.00 Accept (Spotlight)
11 6.00 Adversarial Lipschitz Regularization 6 6 6 0.00 Accept (Poster)
11 6.00 Meta Reinforcement Learning With Autonomous Inference Of Subtask Dependencies 6 6 6 0.00 Accept (Poster)
11 6.00 Deformable Kernels: Adapting Effective Receptive Fields For Object Deformation 6 6 6 0.00 Accept (Poster)
11 6.00 Incorporating Bert Into Neural Machine Translation 6 6 6 0.00 Accept (Poster)
11 6.00 Distance-based Learning From Errors For Confidence Calibration 6 6 6 0.00 Accept (Poster)
11 6.00 Dividemix: Learning With Noisy Labels As Semi-supervised Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Projection Based Constrained Policy Optimization 6 6 6 0.00 Accept (Poster)
11 6.00 Adversarial Policies: Attacking Deep Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 One-shot Pruning Of Recurrent Neural Networks By Jacobian Spectrum Evaluation 6 6 6 0.00 Accept (Poster)
11 6.00 Sampling-free Learning Of Bayesian Quantized Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Understanding Generalization In Recurrent Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Graph Constrained Reinforcement Learning For Natural Language Action Spaces 6 6 6 0.00 Accept (Poster)
11 6.00 Spikegrad: An Ann-equivalent Computation Model For Implementing Backpropagation With Spikes 6 6 6 0.00 Accept (Poster)
11 6.00 Extracting And Leveraging Feature Interaction Interpretations 6 6 6 0.00 Accept (Poster)
11 6.00 Gradient Regularization For Quantization Robustness 6 6 6 0.00 Accept (Poster)
11 6.00 Masked Based Unsupervised Content Transfer 6 6 6 0.00 Accept (Poster)
11 6.00 A Framework For Robustness Certification Of Smoothed Classifiers Using F-divergences 6 6 6 0.00 Accept (Poster)
11 6.00 V-mpo: On-policy Maximum A Posteriori Policy Optimization For Discrete And Continuous Control 6 6 6 0.00 Accept (Poster)
11 6.00 Mixed Precision Dnns: All You Need Is A Good Parametrization 6 6 6 0.00 Accept (Poster)
11 6.00 Thinking While Moving: Deep Reinforcement Learning With Concurrent Control 6 6 6 0.00 Accept (Poster)
11 6.00 Don’t Use Large Mini-batches, Use Local Sgd 6 6 6 0.00 Accept (Poster)
11 6.00 Keep Doing What Worked: Behavior Modelling Priors For Offline Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Imitation Learning Via Off-policy Distribution Matching 6 6 6 0.00 Accept (Poster)
11 6.00 Empirical Bayes Transductive Meta-learning With Synthetic Gradients 6 6 6 0.00 Accept (Poster)
11 6.00 On The Relationship Between Self-attention And Convolutional Layers 6 6 6 0.00 Accept (Poster)
11 6.00 A Closer Look At The Optimization Landscapes Of Generative Adversarial Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Unsupervised Clustering Using Pseudo-semi-supervised Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Adversarial Autoaugment 6 6 6 0.00 Accept (Poster)
11 6.00 Dynamic Model Pruning With Feedback 6 6 6 0.00 Accept (Poster)
11 6.00 Understanding The Limitations Of Variational Mutual Information Estimators 6 6 6 0.00 Accept (Poster)
11 6.00 Deep Semi-supervised Anomaly Detection 6 6 6 0.00 Accept (Poster)
11 6.00 Graph Convolutional Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Understanding The Limitations Of Conditional Generative Models 6 6 6 0.00 Accept (Poster)
11 6.00 Scalable Neural Methods For Reasoning With A Symbolic Knowledge Base 6 6 6 0.00 Accept (Poster)
11 6.00 Graphaf: A Flow-based Autoregressive Model For Molecular Graph Generation 6 6 6 0.00 Accept (Poster)
11 6.00 Evaluating The Search Phase Of Neural Architecture Search 6 6 6 0.00 Accept (Poster)
11 6.00 Adversarial Example Detection And Classification With Asymmetrical Adversarial Training 6 6 6 0.00 Accept (Poster)
11 6.00 Adaptive Structural Fingerprints For Graph Attention Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality 6 6 6 0.00 Accept (Poster)
11 6.00 On Universal Equivariant Set Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Option Discovery Using Deep Skill Chaining 6 6 6 0.00 Accept (Poster)
11 6.00 Unpaired Point Cloud Completion On Real Scans Using Adversarial Training 6 6 6 0.00 Accept (Poster)
11 6.00 Jelly Bean World: A Testbed For Never-ending Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Deep Probabilistic Subsampling For Task-adaptive Compressed Sensing 6 6 6 0.00 Accept (Poster)
11 6.00 Residual Energy-based Models For Text Generation 6 6 6 0.00 Accept (Poster)
11 6.00 State-only Imitation With Transition Dynamics Mismatch 6 6 6 0.00 Accept (Poster)
11 6.00 Deep Graph Matching Consensus 6 6 6 0.00 Accept (Poster)
11 6.00 Unsupervised Model Selection For Variational Disentangled Representation Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Slomo: Improving Communication-efficient Distributed Sgd With Slow Momentum 6 6 6 0.00 Accept (Poster)
11 6.00 Learning Self-correctable Policies And Value Functions From Demonstrations With Negative Sampling 6 6 6 0.00 Accept (Poster)
11 6.00 Cophy: Counterfactual Learning Of Physical Dynamics 6 6 6 0.00 Accept (Spotlight)
11 6.00 The Gambler’s Problem And Beyond 6 6 6 0.00 Accept (Poster)
11 6.00 Structured Object-aware Physics Prediction For Video Modeling And Planning 6 6 6 0.00 Accept (Poster)
11 6.00 Combining Q-learning And Search With Amortized Value Estimates 6 6 6 0.00 Accept (Poster)
11 6.00 Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints 6 6 6 0.00 Accept (Poster)
11 6.00 Robust And Interpretable Blind Image Denoising Via Bias-free Convolutional Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Vid2game: Controllable Characters Extracted From Real-world Videos 6 6 6 0.00 Accept (Poster)
11 6.00 Infinite-horizon Differentiable Model Predictive Control 6 6 6 0.00 Accept (Poster)
11 6.00 Advectivenet: An Eulerian-lagrangian Fluidic Reservoir For Point Cloud Processing 6 6 6 0.00 Accept (Poster)
11 6.00 Once For All: Train One Network And Specialize It For Efficient Deployment 6 6 6 0.00 Accept (Poster)
11 6.00 Graph Inference Learning For Semi-supervised Classification 6 6 6 0.00 Accept (Poster)
11 6.00 Theory And Evaluation Metrics For Learning Disentangled Representations 6 6 6 0.00 Accept (Poster)
11 6.00 The Implicit Bias Of Depth: How Incremental Learning Drives Generalization 6 6 6 0.00 Accept (Poster)
11 6.00 A Stochastic Derivative Free Optimization Method With Momentum 6 6 6 0.00 Accept (Poster)
11 6.00 Stochastic Auc Maximization With Deep Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Metapix: Few-shot Video Retargeting 6 6 6 0.00 Accept (Poster)
11 6.00 Videoflow: A Conditional Flow-based Model For Stochastic Video Generation 6 6 6 0.00 Accept (Poster)
11 6.00 Scalable Object-oriented Sequential Generative Models 6 6 6 0.00 Accept (Poster)
11 6.00 Mixup Inference: Better Exploiting Mixup To Defend Adversarial Attacks 6 6 6 0.00 Accept (Poster)
11 6.00 Conservative Uncertainty Estimation By Fitting Prior Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Rapp: Novelty Detection With Reconstruction Along Projection Pathway 6 6 6 0.00 Accept (Poster)
11 6.00 Novelty Detection Via Blurring 6 6 6 0.00 Accept (Poster)
11 6.00 Detecting Extrapolation With Local Ensembles 6 6 6 0.00 Accept (Poster)
11 6.00 Learning To Solve The Credit Assignment Problem 6 6 6 0.00 Accept (Poster)
11 6.00 Pac Confidence Sets For Deep Neural Networks Via Calibrated Prediction 6 6 6 0.00 Accept (Poster)
11 6.00 Dynamical Distance Learning For Semi-supervised And Unsupervised Skill Discovery 6 6 6 0.00 Accept (Poster)
11 6.00 The Local Elasticity Of Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Infograph: Unsupervised And Semi-supervised Graph-level Representation Learning Via Mutual Information Maximization 6 6 6 0.00 Accept (Spotlight)
11 6.00 Are Transformers Universal Approximators Of Sequence-to-sequence Functions? 6 6 6 0.00 Accept (Poster)
11 6.00 Stochastic Conditional Generative Networks With Basis Decomposition 6 6 6 0.00 Accept (Poster)
11 6.00 Attributes Obfuscation With Complex-valued Features 6 6 6 0.00 Accept (Poster)
11 6.00 Composition-based Multi-relational Graph Convolutional Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Structpool: Structured Graph Pooling Via Conditional Random Fields 6 6 6 0.00 Accept (Poster)
11 6.00 On Generalization Error Bounds Of Noisy Gradient Methods For Non-convex Learning 6 6 6 0.00 Accept (Poster)
11 6.00 A Target-agnostic Attack On Deep Models: Exploiting Security Vulnerabilities Of Transfer Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Meta-learning Curiosity Algorithms 6 6 6 0.00 Accept (Poster)
11 6.00 On Computation And Generalization Of Gener- Ative Adversarial Imitation Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Unrestricted Adversarial Examples Via Semantic Manipulation 6 6 6 0.00 Accept (Poster)
11 6.00 Towards Neural Networks That Provably Know When They Don’t Know 6 6 6 0.00 Accept (Poster)
11 6.00 Exploration In Reinforcement Learning With Deep Covering Options 6 6 6 0.00 Accept (Poster)
11 6.00 A Baseline For Few-shot Image Classification 6 6 6 0.00 Accept (Poster)
11 6.00 Towards Fast Adaptation Of Neural Architectures With Meta Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Cross-domain Few-shot Classification Via Learned Feature-wise Transformation 6 6 6 0.00 Accept (Spotlight)
11 6.00 Learning To Move With Affordance Maps 6 6 6 0.00 Accept (Poster)
11 6.00 Cm3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 To Relieve Your Headache Of Training An Mrf, Take Advil 6 6 6 0.00 Accept (Poster)
11 6.00 Analysis Of Video Feature Learning In Two-stream Cnns On The Example Of Zebrafish Swim Bout Classification 6 6 6 0.00 Accept (Poster)
11 6.00 Beyond Linearization: On Quadratic And Higher-order Approximation Of Wide Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Conditional Learning Of Fair Representations 6 6 6 0.00 Accept (Spotlight)
11 6.00 Curvature Graph Network 6 6 6 0.00 Accept (Poster)
11 6.00 Pruned Graph Scattering Transforms 6 6 6 0.00 Accept (Poster)
11 6.00 The Curious Case Of Neural Text Degeneration 6 6 6 0.00 Accept (Poster)
11 6.00 Graphsaint: Graph Sampling Based Inductive Learning Method 6 6 6 0.00 Accept (Poster)
11 6.00 Learning To Coordinate Manipulation Skills Via Skill Behavior Diversification 6 6 6 0.00 Accept (Poster)
11 6.00 Expected Information Maximization: Using The I-projection For Mixture Density Estimation 6 6 6 0.00 Accept (Poster)
11 6.00 Generative Ratio Matching Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Composing Task-agnostic Policies With Deep Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Selection Via Proxy: Efficient Data Selection For Deep Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Frequency-based Search-control In Dyna 6 6 6 0.00 Accept (Poster)
11 6.00 Demystifying Inter-class Disentanglement 6 6 6 0.00 Accept (Poster)
11 6.00 Continual Learning With Bayesian Neural Networks For Non-stationary Data 6 6 6 0.00 Accept (Poster)
11 6.00 Inductive And Unsupervised Representation Learning On Graph Structured Objects 6 6 6 0.00 Accept (Poster)
11 6.00 Picking Winning Tickets Before Training By Preserving Gradient Flow 6 6 6 0.00 Accept (Poster)
11 6.00 Certified Defenses For Adversarial Patches 6 6 6 0.00 Accept (Poster)
11 6.00 Multilingual Alignment Of Contextual Word Representations 6 6 6 0.00 Accept (Poster)
11 6.00 Black-box Off-policy Estimation For Infinite-horizon Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Compositional Languages Emerge In A Neural Iterated Learning Model 6 6 6 0.00 Accept (Poster)
11 6.00 Rethinking The Hyperparameters For Fine-tuning 6 6 6 0.00 Accept (Poster)
11 6.00 The Shape Of Data: Intrinsic Distance For Data Distributions 6 6 6 0.00 Accept (Poster)
11 6.00 On The Global Convergence Of Training Deep Linear Resnets 6 6 6 0.00 Accept (Poster)
11 6.00 Action Semantics Network: Considering The Effects Of Actions In Multiagent Systems 6 6 6 0.00 Accept (Poster)
11 6.00 Curriculum Loss: Robust Learning And Generalization Against Label Corruption 6 6 6 0.00 Accept (Poster)
11 6.00 Tensor Decompositions For Temporal Knowledge Base Completion 6 6 6 0.00 Accept (Poster)
11 6.00 Towards Better Understanding Of Adaptive Gradient Algorithms In Generative Adversarial Nets 6 6 6 0.00 Accept (Poster)
11 6.00 Why Not To Use Zero Imputation? Correcting Sparsity Bias In Training Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Enabling Deep Spiking Neural Networks With Hybrid Conversion And Spike Timing Dependent Backpropagation 6 6 6 0.00 Accept (Poster)
11 6.00 Deep Audio Priors Emerge From Harmonic Convolutional Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Binaryduo: Reducing Gradient Mismatch In Binary Activation Network By Coupling Binary Activations 6 6 6 0.00 Accept (Poster)
11 6.00 Pseudo-lidar++: Accurate Depth For 3d Object Detection In Autonomous Driving 6 6 6 0.00 Accept (Poster)
11 6.00 Adjustable Real-time Style Transfer 6 6 6 0.00 Accept (Poster)
11 6.00 You Only Train Once: Loss-conditional Training Of Deep Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Progressive Memory Banks For Incremental Domain Adaptation 6 6 6 0.00 Accept (Poster)
11 6.00 Certified Robustness For Top-k Predictions Against Adversarial Perturbations Via Randomized Smoothing 6 6 6 0.00 Accept (Poster)
11 6.00 Deep Orientation Uncertainty Learning Based On A Bingham Loss 6 6 0.00 Accept (Poster)
11 6.00 Caql: Continuous Action Q-learning 6 6 0.00 Accept (Poster)
11 6.00 Identifying Through Flows For Recovering Latent Representations 6 6 0.00 Accept (Poster)
11 6.00 Reinforced Active Learning For Image Segmentation 6 6 0.00 Accept (Poster)
11 6.00 Towards A Deep Network Architecture For Structured Smoothness 6 6 0.00 Accept (Poster)
11 6.00 The Variational Bandwidth Bottleneck: Stochastic Evaluation On An Information Budget 6 6 0.00 Accept (Poster)
11 6.00 Bounds On Over-parameterization For Guaranteed Existence Of Descent Paths In Shallow Relu Networks 6 6 0.00 Accept (Poster)
11 6.00 On Bonus Based Exploration Methods In The Arcade Learning Environment 6 6 0.00 Accept (Poster)
11 6.00 Hierarchical Foresight: Self-supervised Learning Of Long-horizon Tasks Via Visual Subgoal Generation 6 6 0.00 Accept (Poster)
12 5.75 Maximum Likelihood Constraint Inference For Inverse Reinforcement Learning 8 6 3 6 3.19 Accept (Spotlight)
12 5.75 Autoq: Automated Kernel-wise Neural Network Quantization 6 6 8 3 3.19 Accept (Poster)
12 5.75 Towards Verified Robustness Under Text Deletion Interventions 3 6 8 6 3.19 Accept (Poster)
12 5.75 Mutual Information Gradient Estimation For Representation Learning 6 3 6 8 3.19 Accept (Poster)
12 5.75 Computation Reallocation For Object Detection 8 6 6 3 3.19 Accept (Poster)
12 5.75 Learning The Difference That Makes A Difference With Counterfactually-augmented Data 8 6 1 8 8.19 Accept (Spotlight)
12 5.75 Varibad: A Very Good Method For Bayes-adaptive Deep Rl Via Meta-learning 8 6 8 1 8.19 Accept (Poster)
12 5.75 Pcmc-net: Feature-based Pairwise Choice Markov Chains 8 6 6 3 3.19 Accept (Poster)
12 5.75 Image-guided Neural Object Rendering 6 3 8 6 3.19 Accept (Poster)
12 5.75 Neural Arithmetic Units 8 3 6 6 3.19 Accept (Spotlight)
12 5.75 Es-maml: Simple Hessian-free Meta Learning 8 8 6 1 8.19 Accept (Poster)
12 5.75 Probability Calibration For Knowledge Graph Embedding Models 6 8 3 6 3.19 Accept (Poster)
12 5.75 Span Recovery For Deep Neural Networks With Applications To Input Obfuscation 3 6 8 6 3.19 Accept (Poster)
12 5.75 White Noise Analysis Of Neural Networks 6 6 8 3 3.19 Accept (Spotlight)
13 5.67 From Inference To Generation: End-to-end Fully Self-supervised Generation Of Human Face From Speech 8 3 6 4.22 Accept (Poster)
13 5.67 Variance Reduction With Sparse Gradients 8 6 3 4.22 Accept (Poster)
13 5.67 Large Batch Optimization For Deep Learning: Training Bert In 76 Minutes 6 8 3 4.22 Accept (Poster)
13 5.67 Robust Local Features For Improving The Generalization Of Adversarial Training 8 3 6 4.22 Accept (Poster)
13 5.67 Watch, Try, Learn: Meta-learning From Demonstrations And Rewards 8 3 6 4.22 Accept (Poster)
13 5.67 Editable Neural Networks 8 3 6 4.22 Accept (Poster)
13 5.67 Prediction Poisoning: Towards Defenses Against Dnn Model Stealing Attacks 3 8 6 4.22 Accept (Poster)
13 5.67 Population-guided Parallel Policy Search For Reinforcement Learning 6 8 3 4.22 Accept (Poster)
13 5.67 Nas Evaluation Is Frustratingly Hard 8 8 1 10.89 Accept (Poster)
13 5.67 Learning Execution Through Neural Code Fusion 3 8 6 4.22 Accept (Poster)
13 5.67 Neural Stored-program Memory 6 8 3 4.22 Accept (Poster)
13 5.67 A Simple Randomization Technique For Generalization In Deep Reinforcement Learning 8 3 6 4.22 Accept (Poster)
13 5.67 On The Weaknesses Of Reinforcement Learning For Neural Machine Translation 8 6 3 4.22 Accept (Poster)
13 5.67 Self: Learning To Filter Noisy Labels With Self-ensembling 3 8 6 4.22 Accept (Poster)
13 5.67 Provable Benefit Of Orthogonal Initialization In Optimizing Deep Linear Networks 6 3 8 4.22 Accept (Poster)
13 5.67 Emergent Tool Use From Multi-agent Autocurricula 3 8 6 4.22 Accept (Spotlight)
13 5.67 Sadam: A Variant Of Adam For Strongly Convex Functions 3 6 8 4.22 Accept (Poster)
13 5.67 Deep Learning Of Determinantal Point Processes Via Proper Spectral Sub-gradient 6 3 8 4.22 Accept (Poster)
13 5.67 Meta Dropout: Learning To Perturb Latent Features For Generalization 6 8 3 4.22 Accept (Poster)
13 5.67 Functional Vs. Parametric Equivalence Of Relu Networks 6 8 3 4.22 Accept (Poster)
13 5.67 Neural Policy Gradient Methods: Global Optimality And Rates Of Convergence 3 6 8 4.22 Accept (Poster)
13 5.67 State Alignment-based Imitation Learning 6 8 3 4.22 Accept (Poster)
13 5.67 Self-supervised Learning Of Appliance Usage 8 3 6 4.22 Accept (Poster)
13 5.67 Finding And Visualizing Weaknesses Of Deep Reinforcement Learning Agents 8 6 3 4.22 Accept (Poster)
13 5.67 Neural Oblivious Decision Ensembles For Deep Learning On Tabular Data 3 8 6 4.22 Accept (Poster)
13 5.67 Model-augmented Actor-critic: Backpropagating Through Paths 3 6 8 4.22 Accept (Poster)
13 5.67 Macer: Attack-free And Scalable Robust Training Via Maximizing Certified Radius 8 6 3 4.22 Accept (Poster)
13 5.67 Behaviour Suite For Reinforcement Learning 8 3 6 4.22 Accept (Spotlight)
13 5.67 Variational Hetero-encoder Randomized Gans For Joint Image-text Modeling 6 8 3 4.22 Accept (Poster)
13 5.67 Bertscore: Evaluating Text Generation With Bert 6 3 8 4.22 Accept (Poster)
13 5.67 Learning To Explore Using Active Neural Mapping 8 3 6 4.22 Accept (Poster)
13 5.67 Learning Transport Cost From Subset Correspondence 8 6 3 4.22 Accept (Poster)
13 5.67 Generative Models For Effective Ml On Private, Decentralized Datasets 8 6 3 4.22 Accept (Poster)
13 5.67 Empirical Studies On The Properties Of Linear Regions In Deep Neural Networks 8 6 3 4.22 Accept (Poster)
13 5.67 Meta-dataset: A Dataset Of Datasets For Learning To Learn From Few Examples 3 6 8 4.22 Accept (Poster)
13 5.67 Compositional Continual Language Learning 3 8 6 4.22 Accept (Poster)
13 5.67 Data-independent Neural Pruning Via Coresets 6 8 3 4.22 Accept (Poster)
13 5.67 Learning Heuristics For Quantified Boolean Formulas Through Reinforcement Learning 6 8 3 4.22 Accept (Poster)
13 5.67 Augmenting Genetic Algorithms With Deep Neural Networks For Exploring The Chemical Space 8 6 3 4.22 Accept (Poster)
13 5.67 A Signal Propagation Perspective For Pruning Neural Networks At Initialization 6 8 3 4.22 Accept (Spotlight)
13 5.67 Neural Tangents: Fast And Easy Infinite Neural Networks In Python 3 8 6 4.22 Accept (Spotlight)
13 5.67 Structbert: Incorporating Language Structures Into Pre-training For Deep Language Understanding 6 8 3 4.22 Accept (Poster)
13 5.67 Nas-bench-1shot1: Benchmarking And Dissecting One-shot Neural Architecture Search 8 8 1 10.89 Accept (Poster)
13 5.67 Adversarially Robust Representations With Smooth Encoders 8 3 6 4.22 Accept (Poster)
13 5.67 Iterative Energy-based Projection On A Normal Data Manifold For Anomaly Localization 8 6 3 4.22 Accept (Poster)
13 5.67 Bridging Mode Connectivity In Loss Landscapes And Adversarial Robustness 6 8 3 4.22 Accept (Poster)
13 5.67 Identity Crisis: Memorization And Generalization Under Extreme Overparameterization 8 3 6 4.22 Accept (Poster)
13 5.67 B-spline Cnns On Lie Groups 6 3 8 4.22 Accept (Poster)
13 5.67 Adversarially Robust Transfer Learning 1 8 8 10.89 Accept (Poster)
13 5.67 Improved Memory In Recurrent Neural Networks With Sequential Non-normal Dynamics 3 8 6 4.22 Accept (Poster)
13 5.67 Towards Stable And Efficient Training Of Verifiably Robust Neural Networks 8 3 6 4.22 Accept (Poster)
13 5.67 Transferring Optimality Across Data Distributions Via Homotopy Methods 6 8 3 4.22 Accept (Poster)
13 5.67 The Asymptotic Spectrum Of The Hessian Of Dnn Throughout Training 3 8 6 4.22 Accept (Poster)
13 5.67 Learn To Explain Efficiently Via Neural Logic Inductive Learning 3 6 8 4.22 Accept (Poster)
13 5.67 Robust Training With Ensemble Consensus 8 6 3 4.22 Accept (Poster)
13 5.67 Domain Adaptive Multiflow Networks 8 6 3 4.22 Accept (Poster)
13 5.67 Distributionally Robust Neural Networks 6 8 3 4.22 Accept (Poster)
13 5.67 Learning To Group: A Bottom-up Framework For 3d Part Discovery In Unseen Categories 3 6 8 4.22 Accept (Poster)
13 5.67 The Early Phase Of Neural Network Training 3 8 6 4.22 Accept (Poster)
13 5.67 Extreme Classification Via Adversarial Softmax Approximation 8 6 3 4.22 Accept (Poster)
13 5.67 Convergence Behaviour Of Some Gradient-based Methods On Bilinear Zero-sum Games 3 8 6 4.22 Accept (Poster)
13 5.67 Gradients As Features For Deep Representation Learning 8 3 6 4.22 Accept (Poster)
13 5.67 Capsules With Inverted Dot-product Attention Routing 3 8 6 4.22 Accept (Poster)
13 5.67 Implicit Bias Of Gradient Descent Based Adversarial Training On Separable Data 6 8 3 4.22 Accept (Poster)
13 5.67 Understanding Architectures Learnt By Cell-based Neural Architecture Search 8 6 3 4.22 Accept (Poster)
13 5.67 Maxmin Q-learning: Controlling The Estimation Bias Of Q-learning 8 6 3 4.22 Accept (Poster)
13 5.67 Kernel Of Cyclegan As A Principal Homogeneous Space 8 6 3 4.22 Accept (Poster)
13 5.67 Neural Execution Of Graph Algorithms 1 8 8 10.89 Accept (Poster)
13 5.67 On Need For Topology-aware Generative Models For Manifold-based Defenses 3 8 6 4.22 Accept (Poster)
13 5.67 Universal Approximation With Certified Networks 6 8 3 4.22 Accept (Poster)
13 5.67 Discovering Motor Programs By Recomposing Demonstrations 3 6 8 4.22 Accept (Poster)
13 5.67 Hypermodels For Exploration 8 3 6 4.22 Accept (Poster)
14 5.50 Sub-policy Adaptation For Hierarchical Reinforcement Learning 3 8 6.25 Accept (Poster)
14 5.50 Pairnorm: Tackling Oversmoothing In Gnns 3 8 6.25 Accept (Poster)
14 5.50 Svqn: Sequential Variational Soft Q-learning Networks 3 8 6.25 Accept (Poster)
14 5.50 Cln2inv: Learning Loop Invariants With Continuous Logic Networks 3 8 6.25 Accept (Poster)
15 5.25 Spatially Parallel Attention And Component Extraction For Scene Decomposition 6 6 3 6 1.69 Accept (Poster)
15 5.25 Impact: Importance Weighted Asynchronous Architectures With Clipped Target Networks 6 3 6 6 1.69 Accept (Poster)
15 5.25 Shifted And Squeezed 8-bit Floating Point Format For Low-precision Training Of Deep Neural Networks 6 8 1 6 6.69 Accept (Poster)
15 5.25 Visual Representation Learning With 3d View-constrastive Inverse Graphics Networks 3 6 6 6 1.69 Accept (Poster)
16 5.00 V4d: 4d Convonlutional Neural Networks For Video-level Representation Learning 3 6 6 2.00 Accept (Poster)
16 5.00 Ranking Policy Gradient 6 3 6 2.00 Accept (Poster)
16 5.00 Regularizing Activations In Neural Networks Via Distribution Matching With The Wassertein Metric 6 6 3 2.00 Accept (Poster)
16 5.00 Cross-lingual Ability Of Multilingual Bert: An Empirical Study 6 6 3 2.00 Accept (Poster)
16 5.00 Abstract Diagrammatic Reasoning With Multiplex Graph Networks 6 3 6 2.00 Accept (Poster)
16 5.00 Augmenting Non-collaborative Dialog Systems With Explicit Semantic And Strategic Dialog History 6 3 6 2.00 Accept (Poster)
16 5.00 Mma Training: Direct Input Space Margin Maximization Through Adversarial Training 6 6 3 2.00 Accept (Poster)
16 5.00 Generalized Convolutional Forest Networks For Domain Generalization And Visual Recognition 6 3 6 2.00 Accept (Poster)
16 5.00 Weakly Supervised Clustering By Exploiting Unique Class Count 8 1 6 8.67 Accept (Poster)
16 5.00 Additive Powers-of-two Quantization: A Non-uniform Discretization For Neural Networks 6 3 6 2.00 Accept (Poster)
16 5.00 Jacobian Adversarially Regularized Networks For Robustness 6 6 3 2.00 Accept (Poster)
16 5.00 Lamol: Language Modeling For Lifelong Language Learning 6 3 6 2.00 Accept (Poster)
16 5.00 Training Recurrent Neural Networks Online By Learning Explicit State Variables 3 6 6 2.00 Accept (Poster)
16 5.00 Relational State-space Model For Stochastic Multi-object Systems 3 6 6 2.00 Accept (Poster)
16 5.00 Stochastic Weight Averaging In Parallel: Large-batch Training That Generalizes Well 3 6 6 2.00 Accept (Poster)
16 5.00 Bayesian Meta Sampling For Fast Uncertainty Adaptation 3 6 6 2.00 Accept (Poster)
16 5.00 Phase Transitions For The Information Bottleneck In Representation Learning 6 3 6 2.00 Accept (Poster)
16 5.00 Neural Text Generation With Unlikelihood Training 3 6 6 2.00 Accept (Poster)
16 5.00 Model-based Reinforcement Learning For Biological Sequence Design 6 3 6 2.00 Accept (Poster)
16 5.00 Depth-adaptive Transformer 6 6 3 2.00 Accept (Poster)
16 5.00 Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers 3 6 6 2.00 Accept (Poster)
16 5.00 Critical Initialisation In Continuous Approximations Of Binary Neural Networks 6 6 3 2.00 Accept (Poster)
16 5.00 Prox-sgd: Training Structured Neural Networks Under Regularization And Constraints 6 6 3 2.00 Accept (Poster)
16 5.00 Bayesopt Adversarial Attack 6 6 3 2.00 Accept (Poster)
16 5.00 Chameleon: Adaptive Code Optimization For Expedited Deep Neural Network Compilation 3 6 6 2.00 Accept (Poster)
16 5.00 Learning Nearly Decomposable Value Functions Via Communication Minimization 6 6 3 2.00 Accept (Poster)
16 5.00 Difference-seeking Generative Adversarial Network–unseen Sample Generation 6 6 3 2.00 Accept (Poster)
16 5.00 Learning Deep Graph Matching With Channel-independent Embedding And Hungarian Attention 6 6 3 2.00 Accept (Poster)
16 5.00 Robust Anomaly Detection And Backdoor Attack Detection Via Differential Privacy 6 6 3 2.00 Accept (Poster)
16 5.00 Robustness Verification For Transformers 6 6 3 2.00 Accept (Poster)
16 5.00 Implementing Inductive Bias For Different Navigation Tasks Through Diverse Rnn Attrractors 3 6 6 2.00 Accept (Poster)
16 5.00 Enhancing Transformation-based Defenses Against Adversarial Attacks With A Distribution Classifier 6 3 6 2.00 Accept (Poster)
16 5.00 Functional Regularisation For Continual Learning With Gaussian Processes 6 6 3 2.00 Accept (Poster)
16 5.00 Toward Evaluating Robustness Of Deep Reinforcement Learning With Continuous Control 6 3 6 2.00 Accept (Poster)
16 5.00 Learning Efficient Parameter Server Synchronization Policies For Distributed Sgd 6 3 6 2.00 Accept (Poster)
16 5.00 Understanding Why Neural Networks Generalize Well Through Gsnr Of Parameters 6 3 6 2.00 Accept (Spotlight)
16 5.00 Smoothness And Stability In Gans 8 6 1 8.67 Accept (Poster)
16 5.00 Plug And Play Language Model: A Simple Baseline For Controlled Language Generation 6 3 6 2.00 Accept (Poster)
16 5.00 A Constructive Prediction Of The Generalization Error Across Scales 1 6 8 8.67 Accept (Poster)
16 5.00 Contrastive Representation Distillation 6 6 3 2.00 Accept (Poster)
16 5.00 Differentiable Learning Of Numerical Rules In Knowledge Graphs 6 6 3 2.00 Accept (Poster)
16 5.00 Infinite-horizon Off-policy Policy Evaluation With Multiple Behavior Policies 3 6 6 2.00 Accept (Poster)
16 5.00 Rgbd-gan: Unsupervised 3d Representation Learning From Natural Image Datasets Via Rgbd Image Synthesis 6 3 6 2.00 Accept (Poster)
16 5.00 Generalization Through Memorization: Nearest Neighbor Language Models 6 6 3 2.00 Accept (Poster)
16 5.00 Decentralized Deep Learning With Arbitrary Communication Compression 6 6 3 2.00 Accept (Poster)
16 5.00 Escaping Saddle Points Faster With Stochastic Momentum 6 3 6 2.00 Accept (Poster)
16 5.00 Linear Symmetric Quantization Of Neural Networks For Low-precision Integer Hardware 3 6 6 2.00 Accept (Poster)
16 5.00 Nesterov Accelerated Gradient And Scale Invariance For Adversarial Attacks 3 6 6 2.00 Accept (Poster)
16 5.00 Scalable And Order-robust Continual Learning With Additive Parameter Decomposition 8 1 6 8.67 Accept (Poster)
16 5.00 Four Things Everyone Should Know To Improve Batch Normalization 6 6 3 2.00 Accept (Poster)
16 5.00 Define: Deep Factorized Input Word Embeddings For Neural Sequence Modeling 6 3 6 2.00 Accept (Poster)
16 5.00 Neural Epitome Search For Architecture-agnostic Network Compression 6 6 3 2.00 Accept (Poster)
16 5.00 Efficient Riemannian Optimization On The Stiefel Manifold Via The Cayley Transform 6 3 6 2.00 Accept (Poster)
16 5.00 Federated Adversarial Domain Adaptation 6 3 6 2.00 Accept (Poster)
16 5.00 How To 0wn The Nas In Your Spare Time 6 3 6 2.00 Accept (Poster)
16 5.00 Deep 3d Pan Via Local Adaptive “t-shaped” Convolutions With Global And Local Adaptive Dilations 3 6 6 2.00 Accept (Poster)
16 5.00 Efficient And Information-preserving Future Frame Prediction And Beyond 3 6 6 2.00 Accept (Poster)
16 5.00 Episodic Reinforcement Learning With Associative Memory 6 3 6 2.00 Accept (Poster)
16 5.00 Higher-order Function Networks For Learning Composable 3d Object Representations 6 3 6 2.00 Accept (Poster)
16 5.00 Atomnas: Fine-grained End-to-end Neural Architecture Search 3 6 6 2.00 Accept (Poster)
16 5.00 Learning Space Partitions For Nearest Neighbor Search 6 6 3 2.00 Accept (Poster)
16 5.00 Few-shot Learning On Graphs Via Super-classes Based On Graph Spectral Measures 6 3 6 2.00 Accept (Poster)
16 5.00 Nonlinearities In Activations Substantially Shape The Loss Surfaces Of Neural Networks 3 6 6 2.00 Accept (Poster)
16 5.00 Global Relational Models Of Source Code 6 3 6 2.00 Accept (Poster)
16 5.00 Improving Neural Language Generation With Spectrum Control 6 3 6 2.00 Accept (Poster)
16 5.00 Batchensemble: An Alternative Approach To Efficient Ensemble And Lifelong Learning 6 6 3 2.00 Accept (Poster)
16 5.00 Differentiable Programming For Physical Simulation 6 3 6 2.00 Accept (Poster)
16 5.00 Duration-of-stay Storage Assignment Under Uncertainty 6 3 6 2.00 Accept (Spotlight)
16 5.00 Locally Constant Networks 3 6 6 2.00 Accept (Poster)
16 5.00 Blockswap: Fisher-guided Block Substitution For Network Compression On A Budget 6 3 6 2.00 Accept (Poster)
16 5.00 Vl-bert: Pre-training Of Generic Visual-linguistic Representations 6 6 3 2.00 Accept (Poster)
16 5.00 Deep Symbolic Superoptimization Without Human Knowledge 6 3 6 2.00 Accept (Poster)
16 5.00 Automatically Discovering And Learning New Visual Categories With Ranking Statistics 6 6 3 2.00 Accept (Poster)
16 5.00 Semantically-guided Representation Learning For Self-supervised Monocular Depth 3 6 6 2.00 Accept (Poster)
17 4.67 Pure And Spurious Critical Points: A Geometric Study Of Linear Networks 3 3 8 5.56 Accept (Poster)
17 4.67 Ae-ot: A New Generative Model Based On Extended Semi-discrete Optimal Transport 3 8 3 5.56 Accept (Poster)
17 4.67 I Am Going Mad: Maximum Discrepancy Competition For Comparing Classifiers Adaptively 3 3 8 5.56 Accept (Poster)
17 4.67 Continual Learning With Adaptive Weights (claw) 3 8 3 5.56 Accept (Poster)
17 4.67 Logic And The 2-simplicial Transformer 8 3 3 5.56 Accept (Poster)
18 4.50 Sign-opt: A Query-efficient Hard-label Adversarial Attack 3 6 2.25 Accept (Poster)
18 4.50 Short And Sparse Deconvolution — A Geometric Approach 3 6 2.25 Accept (Poster)
19 4.33 Learning To Represent Programs With Property Signatures 1 6 6 5.56 Accept (Poster)
19 4.33 Disentangling Factors Of Variations Using Few Labels 6 6 1 5.56 Accept (Poster)
19 4.33 Empir: Ensembles Of Mixed Precision Deep Networks For Increased Robustness Against Adversarial Attacks 1 6 6 5.56 Accept (Poster)
19 4.33 Non-autoregressive Dialog State Tracking 6 1 6 5.56 Accept (Poster)
19 4.33 Going Beyond Token-level Pre-training For Embedding-based Large-scale Retrieval 1 6 6 5.56 Accept (Poster)
19 4.33 A Critical Analysis Of Self-supervision, Or What We Can Learn From A Single Image 6 1 6 5.56 Accept (Poster)
19 4.33 Overlearning Reveals Sensitive Attributes 6 1 6 5.56 Accept (Poster)
20 4.00 Exploratory Not Explanatory: Counterfactual Analysis Of Saliency Maps For Deep Rl 1 3 8 8.67 Accept (Poster)
20 4.00 Gap-aware Mitigation Of Gradient Staleness 6 3 3 2.00 Accept (Poster)
20 4.00 Input Complexity And Out-of-distribution Detection With Likelihood-based Generative Models 6 3 3 2.00 Accept (Poster)
20 4.00 Size-free Generalization Bounds For Convolutional Neural Networks 6 3 3 2.00 Accept (Poster)
20 4.00 Fair Resource Allocation In Federated Learning 3 3 6 2.00 Accept (Poster)
20 4.00 Dropedge: Towards Deep Graph Convolutional Networks On Node Classification 6 3 3 2.00 Accept (Poster)
20 4.00 Provable Filter Pruning For Efficient Neural Networks 3 6 3 2.00 Accept (Poster)
20 4.00 Playing The Lottery With Rewards And Multiple Languages: Lottery Tickets In Rl And Nlp 3 3 6 2.00 Accept (Poster)
21 3.33 Few-shot Text Classification With Distributional Signatures 6 1 3 4.22 Accept (Poster)
22 2.33 Efficient Probabilistic Logic Reasoning With Graph Neural Networks 1 3 3 0.89 Accept (Poster)