multi-armed bandit

On Optimal Robustness to Adversarial Corruption in Online Decision Problems NeurIPS 2021 Optimal Algorithms for Range Searching over Multi-Armed Bandits IJCAI 2021 Optimal Best-Arm Identification Methods for Tail-Risk Measures NeurIPS 2021 Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization ICML 2021 Optimal Streaming Algorithms for Multi-Armed Bandits ICML 2021 Parameter-Free Multi-Armed Bandit Algorithms with Hybrid Data-Dependent Regret Bounds COLT 2021 Parametric Graph for Unimodal Ranking Bandit ICML 2021 Preference-based Online Learning with Dueling Bandits: A Survey JMLR 2021 Probabilistic Sequential Shrinking: A Best Arm Identification Algorithm for Stochastic Bandits with Corruptions ICML 2021 Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits AISTATS 2021 Problem Dependent View on Structured Thresholding Bandit Problems ICML 2021 Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature NeurIPS 2021 Pure Exploration in Kernel and Neural Bandits NeurIPS 2021 Quantile Bandits for Best Arms Identification ICML 2021 Quantum Exploration Algorithms for Multi-Armed Bandits AAAI 2021 Rebounding Bandits for Modeling Satiation Effects NeurIPS 2021 Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits NeurIPS 2021 Refined approachability algorithms and application to regret minimization with global costs JMLR 2021 Regime Switching Bandits NeurIPS 2021 Regret Bounds for Batched Bandits AAAI 2021 Regret Minimization in Heavy-Tailed Bandits COLT 2021 Regulating Greed Over Time in Multi-Armed Bandits JMLR 2021 Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism ICML 2021 Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits AAAI 2021 Reward Biased Maximum Likelihood Estimation for Reinforcement Learning L4DC 2021