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An information-theoretic analysis of Thompson sampling. (2014)
by
Daniel Russo
,
Benjamin Van Roy
| Citations: | 4 - 1 self |
BibTeX
@MISC{Russo14aninformation-theoretic,
author = {Daniel Russo and Benjamin Van Roy},
title = {An information-theoretic analysis of Thompson sampling.},
year = {2014}
}
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Abstract
Abstract We provide an information-theoretic analysis of Thompson sampling that applies across a broad range of online optimization problems in which a decision-maker must learn from partial feedback. This analysis inherits the simplicity and elegance of information theory and leads to regret bounds that scale with the entropy of the optimal-action distribution. This strengthens preexisting results and yields new insight into how information improves performance.
