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Discrete Component Analysis
Zupan, Eva (Author), Saje, Miran (Author), Zupan, Dejan (Author), Buntine, Wray (Author), Jakulin, Aleks (Author)

URLURL - Presentation file, Visit http://eprints.fri.uni-lj.si/207/ This link opens in a new window

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.

Language:Unknown
Keywords:discrete component analysis, dimension reduction, clustering, principal component analysis, independent component analysis
Work type:Not categorized (r6)
Organization:FRI - Faculty of computer and information science
Year:2006
Publisher:Springer-Verlag
Number of pages:1-33
Views:556
Downloads:187
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