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A Hierarchical Infinite Generalized Dirichlet Mixture Model with Feature Selection
Conference proceeding   Peer reviewed

A Hierarchical Infinite Generalized Dirichlet Mixture Model with Feature Selection

Wentao Fan, Hassen Sallay, Nizar Bouguila and Sami Bourouis
ADAPTIVE AND INTELLIGENT SYSTEMS, ICAIS 2014, Vol.8779, pp.1-10
Lecture Notes in Artificial Intelligence
01/01/2014
DOI: https://doi.org/10.1007/978-3-319-11298-5_1

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Interdisciplinary Applications Science & Technology Technology
We propose a nonparametric Bayesian approach, based on hierarchical Dirichlet processes and generalized Dirichlet distributions, for simultaneous clustering and feature selection. The resulting statistical model is learned within a variational framework that we have developed. The merits of the developed model are shown via extensive simulations and experiments when applied to the challenging problem of images categorization.

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