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Conference Papers Year : 2022

An online Minorization-Maximization algorithm

Abstract

Modern statistical and machine learning settings often involve high data volume and data streaming, which require the development of online estimation algorithms. The online Expectation-Maximization (EM) algorithm extends the popular EM algorithm to this setting, via a stochastic approximation approach. We show that an online version of the Minorization-Maximization (MM) algorithm, which includes the online EM algorithm as a special case, can also be constructed in a similar manner. We demonstrate our approach via an application to the logistic regression problem and compare it to existing methods.
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Dates and versions

hal-03542180 , version 1 (25-01-2022)

Identifiers

  • HAL Id : hal-03542180 , version 1

Cite

Hien Duy Nguyen, Florence Forbes, Gersende Fort, Olivier Cappé. An online Minorization-Maximization algorithm. 17th Conference of the International Federation of Classification Societies, Jul 2022, Porto, Portugal. ⟨hal-03542180⟩
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