Self-accelerated Thompson sampling with near-optimal regret upper bound
Author:
Funder
National Science Foundation of China
Publisher
Elsevier BV
Subject
Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications
Reference27 articles.
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2. Regret analysis of stochastic and nonstochastic multi-armed bandit problems;Bubeck;Found. Trends® Mach. Learn.,2012
3. A numerical analysis of allocation strategies for the multi-armed Bandit problem under delayed rewards conditions in digital campaign management;Martín;Neurocomputing,2019
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5. An empirical evaluation of thompson sampling;Chapelle,2011
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