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Online k-MLE for Mixture Modeling with Exponential Families

  • Christophe Saint-JeanEmail author
  • Frank Nielsen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9389)

Abstract

This paper address the problem of online learning finite statistical mixtures of exponential families. A short review of the Expectation-Maximization (EM) algorithm and its online extensions is done. From these extensions and the description of the k-Maximum Likelihood Estimator (k-MLE), three online extensions are proposed for this latter. To illustrate them, we consider the case of mixtures of Wishart distributions by giving details and providing some experiments.

Keywords

Mixture modeling Online learning k-MLE Wishart distribution 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Mathématiques, Image, Applications (MIA)Université de La RochelleLa RochelleFrance
  2. 2.LIXÉcole PolytechniquePalaiseauFrance

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