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Concentration and confidence for discrete Bayesian sequence predictors

Lattimore, Tor; Hutter, Marcus; Sunehag, Peter


Bayesian sequence prediction is a simple technique for predicting future symbols sampled from an unknown measure on infinite sequences over a countable alphabet. While strong bounds on the expected cumulative error are known, there are only limited results on the distribution of this error. We prove tight high-probability bounds on the cumulative error, which is measured in terms of the Kullback-Leibler (KL) divergence. We also consider the problem of constructing upper confidence bounds on the...[Show more]

CollectionsANU Research Publications
Date published: 2013-10-06
Type: Conference paper
DOI: 10.1007/978-3-642-40935-6_23


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