Learning Theory

Lipschitz and Comparator-Norm Adaptivity in Online Learning COLT 2020 Locally Private Hypothesis Selection COLT 2020 Location Attention for Extrapolation to Longer Sequences ACL 2020 Logarithmic Pruning is All You Need NeurIPS 2020 Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems NeurIPS 2020 Logarithmic Regret for Adversarial Online Control ICML 2020 Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently ICML 2020 LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning IJCAI 2020 Lower Bounds for Learning Distributions under Communication Constraints via Fisher Information JMLR 2020 Lower Bounds for Testing Graphical Models: Colorings and Antiferromagnetic Ising Models JMLR 2020 Making Non-Stochastic Control (Almost) as Easy as Stochastic NeurIPS 2020 Margins are Insufficient for Explaining Gradient Boosting NeurIPS 2020 Maximum-and-Concatenation Networks ICML 2020 Memoryless Sequences for General Losses JMLR 2020 Meta-learning with Stochastic Linear Bandits ICML 2020 MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation CVPR 2020 Minimal Learning Machine: Theoretical Results and Clustering-Based Reference Point Selection JMLR 2020 Minimax Bounds for Generalized Linear Models NeurIPS 2020 Minimax Bounds for Structured Prediction Based on Factor Graphs AISTATS 2020 Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks NeurIPS 2020 Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation ICML 2020 Minimax Rate for Learning From Pairwise Comparisons in the BTL Model ICML 2020 Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition NeurIPS 2020 Minimizing Dynamic Regret and Adaptive Regret Simultaneously AISTATS 2020 Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity NeurIPS 2020