regret bound

Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space NeurIPS 2023 Benefits of monotonicity in safe exploration with Gaussian processes UAI 2023 Best of Both Worlds Policy Optimization ICML 2023 Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm COLT 2023 Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds COLT 2023 Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration & Planning AAAI 2023 Block-Coordinate Methods and Restarting for Solving Extensive-Form Games NeurIPS 2023 Bounding the optimal value function in compositional reinforcement learning UAI 2023 Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits NeurIPS 2023 Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers? JMLR 2023 Cascading Bandits: Optimizing Recommendation Frequency in Delayed Feedback Environments NeurIPS 2023 Cascading Contextual Assortment Bandits NeurIPS 2023 Combinatorial categorized bandits with expert rankings UAI 2023 Combinatorial Causal Bandits AAAI 2023 Combinatorial Neural Bandits ICML 2023 Communication-Constrained Bandits under Additive Gaussian Noise ICML 2023 Competing against Adaptive Strategies in Online Learning via Hints AISTATS 2023 Competing Bandits in Time Varying Matching Markets L4DC 2023 Competing for Shareable Arms in Multi-Player Multi-Armed Bandits ICML 2023 Complexity Analysis of a Countable-armed Bandit Problem ALT 2023 Concurrent Shuffle Differential Privacy Under Continual Observation ICML 2023 Constrained Efficient Global Optimization of Expensive Black-box Functions ICML 2023 Context-lumpable stochastic bandits NeurIPS 2023 Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms COLT 2023 Contextual Bandits and Imitation Learning with Preference-Based Active Queries NeurIPS 2023