A new approach for high-dimensional unsupervised learning: applications to image restoration

Authors:
Nizar Bouguila;Djemel Ziou
Affiliations:
Département d’Informatique, Faculté des Sciences, Université de Sherbrooke, Sherbrooke, Qc, Canada;Département d’Informatique, Faculté des Sciences, Université de Sherbrooke, Sherbrooke, Qc, Canada
Venue:
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Year:
2005

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Abstract

This paper proposes an unsupervised algorithm for learning a high-dimensional finite generalized Dirichlet mixture model. The generalized Dirichlet distribution offers high flexibility and ease of use. We propose a hybrid stochastic expectation maximization algorithm (HSEM) to estimate the parameters of the generalized Dirichlet mixture. The performance of our method is tested by applying it to the problems of image restoration.