Learning Theory

Model-Based Reinforcement Learning with Value-Targeted Regression ICML 2020 Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020 Monte Carlo Gradient Estimation in Machine Learning JMLR 2020 Monte-Carlo Graph Search: the Value of Merging Similar States ACML 2020 More Accurate Learning of k-DNF Reference Classes AAAI 2020 More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models ICML 2020 MOReL: Model-Based Offline Reinforcement Learning NeurIPS 2020 Multi-Feedback Bandit Learning with Probabilistic Contexts IJCAI 2020 Multinomial Logit Bandit with Low Switching Cost ICML 2020 Multi-Stage Influence Function NeurIPS 2020 MuTual: A Dataset for Multi-Turn Dialogue Reasoning ACL 2020 Mutual exclusivity as a challenge for deep neural networks NeurIPS 2020 NAS evaluation is frustratingly hard ICLR 2020 Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs IJCAI 2020 Near-optimal Regret Bounds for Stochastic Shortest Path ICML 2020 Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures ICML 2020 Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals NeurIPS 2020 Near-Tight Margin-Based Generalization Bounds for Support Vector Machines ICML 2020 Neural Anisotropy Directions NeurIPS 2020 Neural Architecture Generator Optimization NeurIPS 2020 Neural Complexity Measures NeurIPS 2020 Neural Networks Learning and Memorization with (almost) no Over-Parameterization NeurIPS 2020 Neural Networks with Small Weights and Depth-Separation Barriers NeurIPS 2020 Neural tangent kernels, transportation mappings, and universal approximation ICLR 2020 New Potential-Based Bounds for Prediction with Expert Advice COLT 2020