Discrete Component Analysis

Wray Buntine and Aleks Jakulin (2006) Discrete Component Analysis. In: Lecture Notes in Computer Science. Volume 3940 / 2006. Subspace, Latent Structure and Feature Selection: Statistical and Optimization Perspectives Workshop, SLSFS 2005, Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers. Springer-Verlag, pp. 1-33.

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Abstract

This article presents a unified theory for analysis of components in discrete data, and compares the methods with techniques such as independent component analysis, non-negative matrix factorisation and latent Dirichlet allocation. The main families of algorithms discussed are a variational approximation, Gibbs sampling, and Rao-Blackwellised Gibbs sampling. Applications are presented for voting records from the United States Senate for 2003, and for the Reuters-21578 newswire collection.

Item Type:

Book Section

Keywords:

discrete component analysis, dimension reduction, clustering, principal component analysis, independent component analysis

Language of Content:

English

Related URLs:

URL	URL Type
http://dx.doi.org/10.1007/11752790_1	Alternative location
http://arxiv.org/abs/math.ST/0604410	Alternative location

Institution:

University of Ljubljana

Department:

Faculty of Computer and Information Science

Divisions:

Faculty of Computer and Information Science > Other

ID Code:

207

Deposited On:

21 Jul 2006

Last Modified:

07 Sep 2008 22:59

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