Multi-Armed Bandits

Is Prior-Free Black-Box Non-Stationary Reinforcement Learning Feasible? AISTATS 2025 Lasso Bandit with Compatibility Condition on Optimal Arm ICLR 2025 LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits AISTATS 2025 Learning from Imperfect Human Feedback: A Tale from Corruption-Robust Dueling ICLR 2025 Learning Personalized Decision Support Policies AAAI 2025 Learning the Pareto Front Using Bootstrapped Observation Samples AISTATS 2025 Linear Streaming Bandit: Regret Minimization and Fixed-Budget Epsilon-Best Arm Identification AAAI 2025 Linear Submodular Maximization with Bandit Feedback AISTATS 2025 Lipschitz Bandits in Optimal Space ICLR 2025 LITE: Efficiently Estimating Gaussian Probability of Maximality AISTATS 2025 Lower Bounds for Time-Varying Kernelized Bandits AISTATS 2025 MARK: Multi-agent Collaboration with Ranking Guidance for Text-attributed Graph Clustering ACL 2025 Minimum Empirical Divergence for Sub-Gaussian Linear Bandits AISTATS 2025 Model selection for behavioral learning data and applications to contextual bandits AISTATS 2025 Multi-agent Multi-armed Bandit Regret Complexity and Optimality AISTATS 2025 Multi-agent Stochastic Bandits Robust to Adversarial Corruptions L4DC 2025 Multi-armed Bandits with Missing Outcomes UAI 2025 Multi-Objective Neural Bandits with Random Scalarization IJCAI 2025 Multi-Player Approaches for Dueling Bandits AISTATS 2025 Multi-play Multi-armed Bandits with Shareable Arm Capacities Revisited: Settling Scarce Capacity ACML 2025 Multiple Trade-offs: An Improved Approach for Lexicographic Linear Bandits AAAI 2025 Multi-thresholding Good Arm Identification with Bandit Feedback ACML 2025 Nearly Tight Bounds for Exploration in Streaming Multi-Armed Bandits with Known Optimality Gap AAAI 2025 Near-Optimal Algorithm for Non-Stationary Kernelized Bandits AISTATS 2025 Near-Optimal Regret Bounds for Federated Multi-armed Bandits with Fully Distributed Communication UAI 2025