An Effective em Algorithm for PCA Mixture Model

Zhong Jin; Franck Davoine; Zhen Lou

An Effective em Algorithm for PCA Mixture Model

Zhong Jin, Franck Davoine, Zhen Lou

Research output: Contribution to journal › Article › Research › peer-review

Abstract

This paper studied PCA mixture model in high dimensional space. A novel EM learning approach by using perturbation was proposed for the PCA mixture model. Experiments showed the novel perturbation EM algorithm is more effective in learning PCA mixture model than an existing constrained EM algorithm. © Springer-Verlag 2004.

Original language	English
Pages (from-to)	626-634
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3138
Publication status	Published - 1 Dec 2004

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title = "An Effective em Algorithm for PCA Mixture Model",

abstract = "This paper studied PCA mixture model in high dimensional space. A novel EM learning approach by using perturbation was proposed for the PCA mixture model. Experiments showed the novel perturbation EM algorithm is more effective in learning PCA mixture model than an existing constrained EM algorithm. {\textcopyright} Springer-Verlag 2004.",

author = "Zhong Jin and Franck Davoine and Zhen Lou",

year = "2004",

month = dec,

day = "1",

language = "English",

volume = "3138",

pages = "626--634",

journal = "Lecture Notes in Computer Science",

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AU - Davoine, Franck

AU - Lou, Zhen

PY - 2004/12/1

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N2 - This paper studied PCA mixture model in high dimensional space. A novel EM learning approach by using perturbation was proposed for the PCA mixture model. Experiments showed the novel perturbation EM algorithm is more effective in learning PCA mixture model than an existing constrained EM algorithm. © Springer-Verlag 2004.

AB - This paper studied PCA mixture model in high dimensional space. A novel EM learning approach by using perturbation was proposed for the PCA mixture model. Experiments showed the novel perturbation EM algorithm is more effective in learning PCA mixture model than an existing constrained EM algorithm. © Springer-Verlag 2004.

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EP - 634

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

ER -

An Effective em Algorithm for PCA Mixture Model

Abstract

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