Learning Theory

Metric Entropy Duality and the Sample Complexity of Outcome Indistinguishability ALT 2022 Minimal Expected Regret in Linear Quadratic Control AISTATS 2022 Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification NeurIPS 2022 Minimax optimal approaches to the label shift problem in non-parametric settings JMLR 2022 Minimax Regret for Cascading Bandits NeurIPS 2022 Minimax Regret on Patterns Using Kullback-Leibler Divergence Covering COLT 2022 Minimax Regret Optimization for Robust Machine Learning under Distribution Shift COLT 2022 Minimizing Control for Credit Assignment with Strong Feedback ICML 2022 Misspecified Phase Retrieval with Generative Priors NeurIPS 2022 Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably) ICML 2022 Model-Free Opponent Shaping ICML 2022 Modeling the Machine Learning Multiverse NeurIPS 2022 Monotone Learning COLT 2022 More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize ICML 2022 Most Activation Functions Can Win the Lottery Without Excessive Depth NeurIPS 2022 Multi-Agent Multi-Armed Bandits with Limited Communication JMLR 2022 Multi-armed Bandit Algorithm against Strategic Replication AISTATS 2022 Multi-Class H-Consistency Bounds NeurIPS 2022 Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes NeurIPS 2022 Multiclass learning with margin: exponential rates with no bias-variance trade-off ICML 2022 Multi-Mode Deep Matrix and Tensor Factorization ICLR 2022 Multi-scale Feature Learning Dynamics: Insights for Double Descent ICML 2022 Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve NeurIPS 2022 Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation AISTATS 2022 Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation ICML 2022