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.
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: |
|Institution: ||University of Ljubljana|
|Department: ||Faculty of Computer and Information Science|
|Divisions: ||Faculty of Computer and Information Science > Other|
|Item ID: ||207|
|Date Deposited: ||21 Jul 2006|
|Last Modified: ||13 Aug 2011 00:32|
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