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Informational Confidence Bounds for Self-Normalized Averages and Applications

We present deviation bounds for self-normalized averages and applications to estimation with a random number of observations. The results rely on a peeling argument in exponential martingale techniques that represents an alternative to the method of mixture. The motivating examples of bandit problems and context tree estimation are detailed.

preprint2013arXivOpen access
Aurélien Garivier
math.STStatistics Theory
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Open access1 author2 topics
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Aurélien Garivier

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