PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

An effective EM algorithm for PCA mixture model
Zhong Jin, Franck Davoine and Zhen Lou
In: Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshops, SSPR 2004 and SPR 2004, August 18-20, 2004, Lisbon, Portugal.

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.

EPrint Type:Conference or Workshop Item (Oral)
Additional Information:Published in Lecture Notes in Computer Science, Volume 3138 / 2004
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:508
Deposited By:Franck Davoine
Deposited On:01 January 2005