thompson sampling

Causal Bandits for Linear Structural Equation Models JMLR 2023 Combinatorial Neural Bandits ICML 2023 Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits AAAI 2023 Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits AISTATS 2023 Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning NeurIPS 2023 Incentivizing Exploration with Linear Contexts and Combinatorial Actions ICML 2023 Information-Directed Selection for Top-Two Algorithms COLT 2023 Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards NeurIPS 2023 Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning ICML 2023 Leveraging Demonstrations to Improve Online Learning: Quality Matters ICML 2023 Mixed-Effect Thompson Sampling AISTATS 2023 Module-wise Adaptive Distillation for Multimodality Foundation Models NeurIPS 2023 Multi-armed bandits for resource efficient, online optimization of language model pre-training: the use case of dynamic masking ACL 2023 Noise-Adaptive Thompson Sampling for Linear Contextual Bandits NeurIPS 2023 Nonstationary Bandit Learning via Predictive Sampling AISTATS 2023 Online Restless Bandits with Unobserved States ICML 2023 Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits ICML 2023 Optimistic Thompson Sampling-based algorithms for episodic reinforcement learning UAI 2023 Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach AISTATS 2023 Probabilistic Inference in Reinforcement Learning Done Right NeurIPS 2023 Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes AISTATS 2023 Stealthy Terrain-Aware Multi-Agent Active Search CoRL 2023 Thompson Exploration with Best Challenger Rule in Best Arm Identification ACML 2023 Thompson Sampling for High-Dimensional Sparse Linear Contextual Bandits ICML 2023 Thompson Sampling with Diffusion Generative Prior ICML 2023