Publication

Alpha-NML Universal Predictors

Michael Christoph Gastpar, Marco Bondaschi
2022
Conference Papers

Abstract

Inspired by Sibson’s alpha-mutual information, we introduce a new parametric class of universal predictors. This class interpolates two well-known predictors, the mixture estimator, that includes the Laplace and the Krichevsky-Trofimov predictors, and the Normalized Maximum Likelihood (NML) estimator. We point out some advantages of this class of predictors and study its performance in terms of known regret measures under logarithmic loss, in particular for the well-studied case of discrete memoryless sources.

Official source

https://infoscience.epfl.ch/entities/publication/2183ad57-b06d-4bd0-bf32-20960220a10d

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Alpha-NML Universal Predictors

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