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 326–350 of 655 papers

TitleStatusHype
GuideBoot: Guided Bootstrap for Deep Contextual Bandits—0
No Regrets for Learning the Prior in Bandits—0
Metalearning Linear Bandits by Prior Update—0
Bayesian decision-making under misspecified priors with applications to meta-learning—0
Markov Decision Process modeled with Bandits for Sequential Decision Making in Linear-flow—0
Random Effect Bandits—0
Thompson Sampling for Unimodal Bandits—0
Thompson Sampling with a Mixture Prior—0
Multi-armed Bandit Algorithms on System-on-Chip: Go Frequentist or Bayesian?—0
A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms—0
Parallelizing Thompson Sampling—0
Kolmogorov-Smirnov Test-Based Actively-Adaptive Thompson Sampling for Non-Stationary Bandits—0
Asymptotically Optimal Bandits under Weighted Information—0
Diffusion Approximations for Thompson Sampling—0
Thompson Sampling for Gaussian Entropic Risk Bandits—0
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep NetworksCode1
Dynamic Slate Recommendation with Gated Recurrent Units and Thompson SamplingCode1
High-dimensional near-optimal experiment design for drug discovery via Bayesian sparse sampling—0
When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution—0
Blind Exploration and Exploitation of Stochastic Experts—0
Challenges in Statistical Analysis of Data Collected by a Bandit Algorithm: An Empirical Exploration in Applications to Adaptively Randomized Experiments—0
Constrained Contextual Bandit Learning for Adaptive Radar Waveform Selection—0
Efficient Optimal Selection for Composited Advertising Creatives with Tree StructureCode0
Automated Creative Optimization for E-Commerce AdvertisingCode0
Online Multi-Armed Bandits with Adaptive Inference—0
Show:102550
← PrevPage 14 of 27Next →

No leaderboard results yet.