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Informational Confidence Bounds for Self-Normalized Averages and Applications
Published 13 Sep 2013 in math.ST and stat.TH | (1309.3376v1)
Abstract: 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.
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