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Thompson Sampling

Thompson sampling, named after William R. Thompson, is a heuristic for choosing actions that addresses the exploration-exploitation dilemma in the multi-armed bandit problem. It consists of choosing the action that maximizes the expected reward with respect to a randomly drawn belief.

Papers

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Showing 301–325 of 655 papers

TitleStatusHype
Risk and optimal policies in bandit experiments—0
Safe Linear Leveling Bandits—0
Doubly Robust Thompson Sampling with Linear Payoffs—0
Observation-Free Attacks on Stochastic Bandits—0
Optimizing Conditional Value-At-Risk of Black-Box FunctionsCode0
Adaptive Gating for Single-Photon 3D Imaging—0
ESCADA: Efficient Safety and Context Aware Dose Allocation for Precision MedicineCode0
Hierarchical Bayesian Bandits—0
The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle—0
Maillard Sampling: Boltzmann Exploration Done Optimally—0
Online Learning of Energy Consumption for Navigation of Electric Vehicles—0
Efficient Inference Without Trading-off Regret in Bandits: An Allocation Probability Test for Thompson Sampling—0
Variational Bayesian Optimistic Sampling—0
Differentially Private Federated Bayesian Optimization with Distributed Exploration—0
Analysis of Thompson Sampling for Partially Observable Contextual Multi-Armed Bandits—0
Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes—0
Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized RecommendationsCode0
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning—0
Batched Thompson Sampling—0
Asymptotic Performance of Thompson Sampling in the Batched Multi-Armed Bandits—0
Expected Improvement-based Contextual Bandits—0
Regularized-OFU: an efficient algorithm for general contextual bandit with optimization oracles—0
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification—0
Deep Exploration for Recommendation Systems—0
Vaccine allocation policy optimization and budget sharing mechanism using Thompson samplingCode0
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