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Thompson Sampling for Stochastic Bandits with Noisy Contexts: An
  Information-Theoretic Regret Analysis

Thompson Sampling for Stochastic Bandits with Noisy Contexts: An Information-Theoretic Regret Analysis

21 January 2024
Sharu Theresa Jose
Shana Moothedath
ArXivPDFHTML

Papers citing "Thompson Sampling for Stochastic Bandits with Noisy Contexts: An Information-Theoretic Regret Analysis"

4 / 4 papers shown
Title
Lifting the Information Ratio: An Information-Theoretic Analysis of
  Thompson Sampling for Contextual Bandits
Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits
Gergely Neu
Julia Olkhovskaya
Matteo Papini
Ludovic Schwartz
65
16
0
27 May 2022
Hierarchical Bayesian Bandits
Hierarchical Bayesian Bandits
Joey Hong
Branislav Kveton
Manzil Zaheer
Mohammad Ghavamzadeh
FedML
72
38
0
12 Nov 2021
Analysis of Thompson Sampling for Partially Observable Contextual
  Multi-Armed Bandits
Analysis of Thompson Sampling for Partially Observable Contextual Multi-Armed Bandits
Yash J. Patel
Mohamad Kazem Shirani Faradonbeh
39
15
0
23 Oct 2021
Thompson Sampling for Contextual Bandits with Linear Payoffs
Thompson Sampling for Contextual Bandits with Linear Payoffs
Shipra Agrawal
Navin Goyal
143
993
0
15 Sep 2012
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