regret bound

An Efficient Algorithm for Fair Multi-Agent Multi-Armed Bandit with Low Regret AAAI 2023 A New Look at Dynamic Regret for Non-Stationary Stochastic Bandits JMLR 2023 An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits NeurIPS 2023 An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits NeurIPS 2023 An Information-Theoretic Analysis of Nonstationary Bandit Learning ICML 2023 Anytime Model Selection in Linear Bandits NeurIPS 2023 A PDE approach for regret bounds under partial monitoring JMLR 2023 Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders NeurIPS 2023 Approximately Stationary Bandits with Knapsacks COLT 2023 A Reduction-based Framework for Sequential Decision Making with Delayed Feedback NeurIPS 2023 A Second-Order Method for Stochastic Bandit Convex Optimisation COLT 2023 A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes NeurIPS 2023 A Tighter Problem-Dependent Regret Bound for Risk-Sensitive Reinforcement Learning AISTATS 2023 A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs COLT 2023 A Unified Approach for Maximizing Continuous DR-submodular Functions NeurIPS 2023 A Unified Model and Dimension for Interactive Estimation NeurIPS 2023 Bandit Multi-linear DR-Submodular Maximization and Its Applications on Adversarial Submodular Bandits ICML 2023 Bandit Online Linear Optimization with Hints and Queries ICML 2023 Bandit problems with fidelity rewards JMLR 2023 Bandit Submodular Maximization for Multi-Robot Coordination in Unpredictable and Partially Observable Environments RSS 2023 Bandits with costly reward observations UAI 2023 Bandits with Knapsacks: Advice on Time-Varying Demands ICML 2023 Bandit Task Assignment with Unknown Processing Time NeurIPS 2023 Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning ICML 2023 Bayesian Design Principles for Frequentist Sequential Learning ICML 2023