SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 526–550 of 655 papers

TitleStatusHype
A Batched Multi-Armed Bandit Approach to News Headline Testing—0
Context in Public Health for Underserved Communities: A Bayesian Approach to Online Restless Bandits—0
A Bayesian Choice Model for Eliminating Feedback Loops—0
Accelerating Grasp Exploration by Leveraging Learned Priors—0
A Change-Detection Based Thompson Sampling Framework for Non-Stationary Bandits—0
Achieving adaptivity and optimality for multi-armed bandits using Exponential-Kullback Leibler Maillard Sampling—0
A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms—0
A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles—0
A Contextual Combinatorial Semi-Bandit Approach to Network Bottleneck Identification—0
A Copula approach for hyperparameter transfer learning—0
A Quantile-based Approach for Hyperparameter Transfer Learning—0
Fast Change Identification in Multi-Play Bandits and its Applications in Wireless Networks—0
Active Reinforcement Learning with Monte-Carlo Tree Search—0
Active Search for High Recall: a Non-Stationary Extension of Thompson Sampling—0
AdaptEx: A Self-Service Contextual Bandit Platform—0
Adaptive Combinatorial Allocation—0
Adaptive Data Augmentation for Thompson Sampling—0
Adaptive Experimentation at Scale: A Computational Framework for Flexible Batches—0
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits—0
Adaptive Gating for Single-Photon 3D Imaging—0
Adaptive Grey-Box Fuzz-Testing with Thompson Sampling—0
Adaptively Learning to Select-Rank in Online Platforms—0
Adaptively Optimize Content Recommendation Using Multi Armed Bandit Algorithms in E-commerce—0
Adaptive Model Selection Framework: An Application to Airline Pricing—0
Adaptive Operator Selection Based on Dynamic Thompson Sampling for MOEA/D—0
Show:102550
← PrevPage 22 of 27Next →

No leaderboard results yet.