Derandomizing stochastic prediction strategies

作者: V. Vovk

DOI: 10.1145/267460.267473

关键词:

摘要: In this paper we continue study of the games prediction with expert advice uncountably many experts. A convenient interpretation such is to construe pool experts as one “stochastic predictor”, who chooses in at random according prior distribution on and then replicates (deterministic ) predictions chosen expert. We notice that if stochastic predictor‘s total loss most L probability least p learner‘s can be bounded by cL + aln \frac{1}{p} for usual constants c a. This used revamp known results obtain new tracking best It also applied merging overconfident fitting polynomials data.

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