linear bandit

Fixed-Budget Best-Arm Identification in Structured Bandits IJCAI 2022 Identifying near-optimal decisions in linear-in-parameter bandit models with continuous decision sets UAI 2022 Improved Pure Exploration in Linear Bandits with No-Regret Learning IJCAI 2022 Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs NeurIPS 2022 Interactively Learning Preference Constraints in Linear Bandits ICML 2022 Linear Bandit Algorithms with Sublinear Time Complexity ICML 2022 Metalearning Linear Bandits by Prior Update AISTATS 2022 Minimax Optimal Fixed-Budget Best Arm Identification in Linear Bandits NeurIPS 2022 Near Instance Optimal Model Selection for Pure Exploration Linear Bandits AISTATS 2022 Norm-Agnostic Linear Bandits AISTATS 2022 Online Learning and Pricing with Reusable Resources: Linear Bandits with Sub-Exponential Rewards ICML 2022 Pareto Optimal Model Selection in Linear Bandits AISTATS 2022 Return of the bias: Almost minimax optimal high probability bounds for adversarial linear bandits COLT 2022 The price of unfairness in linear bandits with biased feedback NeurIPS 2022 Thompson Sampling with a Mixture Prior AISTATS 2022 When Are Linear Stochastic Bandits Attackable? ICML 2022 Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously ICML 2021 Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs NeurIPS 2021 Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification NeurIPS 2021 Decentralized Multi-Agent Linear Bandits with Safety Constraints AAAI 2021 Disposable Linear Bandits for Online Recommendations AAAI 2021 Dynamic Balancing for Model Selection in Bandits and RL ICML 2021 Experimental Design for Regret Minimization in Linear Bandits AISTATS 2021 Impact of Representation Learning in Linear Bandits ICLR 2021 Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP NeurIPS 2021