Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning. Provable Convergence and Global Optimality of Generative Adversarial Network. Representation Learning with Multisets. Deep Gradient Boosting – Layer-wise Input Normalization of Neural Networks. Inferring Dynamical Systems with Long-Range Dependencies through Line …

A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning. Continual Density Ratio Estimation (CDRE): A new method for evaluating generative models in continual learning. Contrastive Representation Distillation. Information-Theoretic Local Minima Characterization and Regularization. Efficient Training of Robust and Verifiable Neural …

Redundancy-Free Computation Graphs for Graph Neural Networks. Towards Effective 2-bit Quantization: Pareto-optimal Bit Allocation for Deep CNNs Compression. Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach. EMS: End-to-End Model Search for Network Architecture, Pruning and Quantization. Out-of-distribution Detec …

Learning scalable and transferable multi-robot/machine sequential assignment planning via graph embedding. Learning Generative Models using Denoising Density Estimators. Invertible generative models for inverse problems: mitigating representation error and dataset bias. XD: Cross-lingual Knowledge Distillation for Polyglot Sentence Embeddings. A Bi …

Phase Transitions for the Information Bottleneck in Representation Learning. DO-AutoEncoder: Learning and Intervening Bivariate Causal Mechanisms in Images. Task-Mediated Representation Learning. Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds. Learning Multi-facet Embeddings of Phrases and Sentences using Sparse Coding for U …

Cross-Lingual Ability of Multilingual BERT: An Empirical Study. Efficient Wrapper Feature Selection using Autoencoder and Model Based Elimination. Knockoff-Inspired Feature Selection via Generative Models. Self-Induced Curriculum Learning in Neural Machine Translation. Granger Causal Structure Reconstruction from Heterogeneous Multivariate Time Ser …

INSTANCE CROSS ENTROPY FOR DEEP METRIC LEARNING. Abstract Diagrammatic Reasoning with Multiplex Graph Networks. MULTIPOLAR: Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse Environmental Dynamics. Semantically-Guided Representation Learning for Self-Supervised Monocular Depth. Generative Integration Networks. Disc …

Improved Structural Discovery and Representation Learning of Multi-Agent Data. Extreme Language Model Compression with Optimal Subwords and Shared Projections. Feature Map Transform Coding for Energy-Efficient CNN Inference. Convergence Analysis of a Momentum Algorithm with Adaptive Step Size for Nonconvex Optimization. Deep Spike Decoder (DSD). Ad …

Incorporating Perceptual Prior to Improve Model’s Adversarial Robustness. Neural Clustering Processes. Bayesian Inference for Large Scale Image Classification. Refining the variational posterior through iterative optimization. Scale-Equivariant Neural Networks with Decomposed Convolutional Filters. Nonlinearities in activations substantially shape …

A⋆MCTS: SEARCH WITH THEORETICAL GUARANTEE USING POLICY AND VALUE FUNCTIONS. FEW-SHOT LEARNING ON GRAPHS VIA SUPER-CLASSES BASED ON GRAPH SPECTRAL MEASURES. DEEP GRAPH SPECTRAL EVOLUTION NETWORKS FOR GRAPH TOPOLOGICAL TRANSFORMATION. Modeling Fake News in Social Networks with Deep Multi-Agent Reinforcement Learning. Long-term planning, short-term ad …

Learning to Reach Goals Without Reinforcement Learning. HOW IMPORTANT ARE NETWORK WEIGHTS? TO WHAT EXTENT DO THEY NEED AN UPDATE?. Universal Adversarial Attack Using Very Few Test Examples. THE EFFECT OF ADVERSARIAL TRAINING: A THEORETICAL CHARACTERIZATION. Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions. Unre …

Learning Invariants through Soft Unification. Collapsed amortized variational inference for switching nonlinear dynamical systems. Thinking While Moving: Deep Reinforcement Learning with Concurrent Control. Target-Embedding Autoencoders for Supervised Representation Learning. COMBINED FLEXIBLE ACTIVATION FUNCTIONS FOR DEEP NEURAL NETWORKS. Neural M …