Multi-Armed Bandits

Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals JMLR 2021 MOTS: Minimax Optimal Thompson Sampling ICML 2021 Multi-armed Bandit Requiring Monotone Arm Sequences NeurIPS 2021 Multi-Armed Bandits with Bounded Arm-Memory: Near-Optimal Guarantees for Best-Arm Identification and Regret Minimization NeurIPS 2021 Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning ICML 2021 Multinomial Logit Contextual Bandits: Provable Optimality and Practicality AAAI 2021 Multiplayer Bandit Learning, from Competition to Cooperation COLT 2021 Near-Optimal MNL Bandits Under Risk Criteria AAAI 2021 Non-Stationary Off-Policy Optimization AISTATS 2021 Non-stationary Reinforcement Learning without Prior Knowledge: an Optimal Black-box Approach COLT 2021 Observation-Free Attacks on Stochastic Bandits NeurIPS 2021 Offline Contextual Bandits with Overparameterized Models ICML 2021 Off-Policy Risk Assessment in Contextual Bandits NeurIPS 2021 Online Limited Memory Neural-Linear Bandits with Likelihood Matching ICML 2021 Online Multi-Armed Bandits with Adaptive Inference NeurIPS 2021 Online Posted Pricing with Unknown Time-Discounted Valuations AAAI 2021 On Multi-Armed Bandit Designs for Dose-Finding Trials JMLR 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 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