minimax optimal

Error Bounds for Learning with Vector-Valued Random Features NeurIPS 2023 Layered State Discovery for Incremental Autonomous Exploration ICML 2023 Matrix Estimation for Individual Fairness ICML 2023 Minimax-Optimal Location Estimation NeurIPS 2023 Minimax optimal testing by classification COLT 2023 Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path ICML 2023 Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes ICML 2023 On Error and Compression Rates for Prototype Rules AAAI 2023 Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization NeurIPS 2023 Recovering Top-Two Answers and Confusion Probability in Multi-Choice Crowdsourcing ICML 2023 Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments ICML 2023 The Aggregation–Heterogeneity Trade-off in Federated Learning COLT 2023 Active Learning with Neural Networks: Insights from Nonparametric Statistics NeurIPS 2022 Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization NeurIPS 2022 An Efficient Minimax Optimal Estimator For Multivariate Convex Regression COLT 2022 Asymptotic Properties for Bayesian Neural Network in Besov Space NeurIPS 2022 Cluster Randomized Designs for One-Sided Bipartite Experiments NeurIPS 2022 Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces ICML 2022 Dynamic Regret of Online Markov Decision Processes ICML 2022 Functional Linear Regression with Mixed Predictors JMLR 2022 Leveraging Initial Hints for Free in Stochastic Linear Bandits ALT 2022 Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture Models NeurIPS 2022 Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling JMLR 2022 Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification NeurIPS 2022 Minimax Optimal Fixed-Budget Best Arm Identification in Linear Bandits NeurIPS 2022