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Thompson Sampling Regret Bounds for Contextual Bandits with sub-Gaussian rewards
26 April 2023
Amaury Gouverneur
Borja Rodríguez Gálvez
T. Oechtering
Mikael Skoglund
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Papers citing
"Thompson Sampling Regret Bounds for Contextual Bandits with sub-Gaussian rewards"
5 / 5 papers shown
Title
An Information-Theoretic Analysis of Bayesian Reinforcement Learning
Amaury Gouverneur
Borja Rodríguez Gálvez
T. Oechtering
Mikael Skoglund
OffRL
61
1
0
18 Jul 2022
Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits
Gergely Neu
Julia Olkhovskaya
Matteo Papini
Ludovic Schwartz
75
16
0
27 May 2022
Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles
Dylan J. Foster
Alexander Rakhlin
365
207
0
12 Feb 2020
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates
Jeffrey Negrea
Mahdi Haghifam
Gintare Karolina Dziugaite
Ashish Khisti
Daniel M. Roy
FedML
153
153
0
06 Nov 2019
Contextual Bandit Learning with Predictable Rewards
Alekh Agarwal
Miroslav Dudík
Satyen Kale
John Langford
Robert Schapire
OffRL
401
86
0
07 Feb 2012
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