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Regret lower bounds and extended Upper Confidence Bounds policies in stochastic multi-armed bandit problem

Regret lower bounds and extended Upper Confidence Bounds policies in stochastic multi-armed bandit problem

Antoine Salomon
Jean-Yves Audibert
I. Alaoui
ArXiv (abs)PDFHTML

Papers citing "Regret lower bounds and extended Upper Confidence Bounds policies in stochastic multi-armed bandit problem"

3 / 3 papers shown
Title
Optimal Regret Bounds for Collaborative Learning in Bandits
Optimal Regret Bounds for Collaborative Learning in Bandits
Amitis Shidani
Sattar Vakili
47
0
0
15 Dec 2023
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
Huasen Wu
Xueying Guo
Xin Liu
54
29
0
12 Sep 2017
Contextual Bandits with Latent Confounders: An NMF Approach
Contextual Bandits with Latent Confounders: An NMF Approach
Rajat Sen
Karthikeyan Shanmugam
Murat Kocaoglu
A. Dimakis
Sanjay Shakkottai
74
4
0
01 Jun 2016

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