thompson sampling

Differentially Private Federated Bayesian Optimization with Distributed Exploration NeurIPS 2021 Doubly Robust Thompson Sampling with Linear Payoffs NeurIPS 2021 Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure AAAI 2021 Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration AAAI 2021 Lenient Regret for Multi-Armed Bandits AAAI 2021 Mercer Features for Efficient Combinatorial Bayesian Optimization AAAI 2021 Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models NeurIPS 2021 Meta-Thompson Sampling ICML 2021 MOTS: Minimax Optimal Thompson Sampling ICML 2021 Multi-Armed Bandits with Cost Subsidy AISTATS 2021 Neural Thompson Sampling ICLR 2021 No Regrets for Learning the Prior in Bandits NeurIPS 2021 Online Multi-Armed Bandits with Adaptive Inference NeurIPS 2021 On Multi-Armed Bandit Designs for Dose-Finding Trials JMLR 2021 On the Suboptimality of Thompson Sampling in High Dimensions NeurIPS 2021 Optimal Thompson Sampling strategies for support-aware CVaR bandits ICML 2021 Optimizing Conditional Value-At-Risk of Black-Box Functions NeurIPS 2021 Parallelizing Thompson Sampling NeurIPS 2021 Reinforcement Learning with Trajectory Feedback AAAI 2021 Scalable Thompson Sampling using Sparse Gaussian Process Models NeurIPS 2021 The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle NeurIPS 2021 Thompson Sampling Algorithms for Cascading Bandits JMLR 2021 Thompson Sampling for Bandits with Clustered Arms IJCAI 2021 Thompson sampling for Markov games with piecewise stationary opponent policies UAI 2021 Toward Optimal Solution for the Context-Attentive Bandit Problem IJCAI 2021