asymptotic optimality

A Model-Free Universal AI UAI 2026 GINO-Q: Learning an Asymptotically Optimal Index Policy for Restless Multi-armed Bandits AAAI 2026 Approximate information maximization for bandit games AISTATS 2025 Best-Arm Identification in Unimodal Bandits AISTATS 2025 On the Asymptotic Optimality of Confidence Interval Based Algorithms for Fixed Confidence MABs AAAI 2025 Consistent Optimal Transport with Empirical Conditional Measures AISTATS 2024 Optimal Batched Linear Bandits ICML 2024 Optimal Weighted Random Forests JMLR 2024 Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic Bandits NeurIPS 2023 Improving the Knowledge Gradient Algorithm NeurIPS 2023 Least Squares Model Averaging for Distributed Data JMLR 2023 Posterior Tracking Algorithm for Classification Bandits AISTATS 2023 Thompson Exploration with Best Challenger Rule in Best Arm Identification ACML 2023 Asymptotically-Optimal Gaussian Bandits with Side Observations ICML 2022 Asymptotically Optimal Locally Private Heavy Hitters via Parameterized Sketches AISTATS 2022 Asymptotic optimality for active learning processes UAI 2022 IMED-RL: Regret optimal learning of ergodic Markov decision processes NeurIPS 2022 Maillard Sampling: Boltzmann Exploration Done Optimally AISTATS 2022 Mean Estimation with User-level Privacy under Data Heterogeneity NeurIPS 2022 Open Problem: Finite-Time Instance Dependent Optimality for Stochastic Online Learning with Feedback Graphs COLT 2022 Reinforcement Learning Augmented Asymptotically Optimal Index Policy for Finite-Horizon Restless Bandits AAAI 2022 Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality NeurIPS 2022 Double Explore-then-Commit: Asymptotic Optimality and Beyond COLT 2021 Lenient Regret for Multi-Armed Bandits AAAI 2021 Optimal Thompson Sampling strategies for support-aware CVaR bandits ICML 2021