thompson sampling

Making RL with Preference-based Feedback Efficient via Randomization ICLR 2024 Meta Learning in Bandits within shared affine Subspaces AISTATS 2024 Near Optimal Adversarial Attacks on Stochastic Bandits and Defenses with Smoothed Responses AISTATS 2024 Online Learning of Decision Trees with Thompson Sampling AISTATS 2024 Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling ICLR 2024 Optimal Exploration is no harder than Thompson Sampling AISTATS 2024 Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds ICML 2024 Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo ICLR 2024 Queueing Matching Bandits with Preference Feedback NeurIPS 2024 Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning NeurIPS 2024 Reinforcement Learning with Lookahead Information NeurIPS 2024 ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages ICML 2024 Sample Efficient Learning of Factored Embeddings of Tensor Fields AISTATS 2024 Speculative Decoding via Early-exiting for Faster LLM Inference with Thompson Sampling Control Mechanism ACL 2024 The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models AAAI 2024 Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox NeurIPS 2024 Thompson Sampling for Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit AAAI 2024 Thompson Sampling Itself is Differentially Private AISTATS 2024 Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits NeurIPS 2024 Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining ICLR 2024 Two-sided Competing Matching Recommendation Markets With Quota and Complementary Preferences Constraints ICML 2024 Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health AAAI 2024 Approximate Thompson Sampling via Epistemic Neural Networks UAI 2023 Batch Bayesian Optimization For Replicable Experimental Design NeurIPS 2023 Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space NeurIPS 2023