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  Brisk Kernel ICA

Jegelka, S., & Gretton, A. (2007). Brisk Kernel ICA. In L. Bottou, O. Chapelle, D. DeCoste, & J. Weston (Eds.), Large Scale Kernel Machines (pp. 225-250). Cambridge, MA, USA: MIT Press.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-CBFF-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-E8EA-0
Genre: Book Chapter

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Jegelka, S1, 2, Author              
Gretton, A1, 2, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Recent approaches to independent component analysis have used kernel independence measures to obtain very good performance in ICA, particularly in areas where classical methods experience difficulty (for instance, sources with near-zero kurtosis). In this chapter, we compare two efficient extensions of these methods for large-scale problems: random subsampling of entries in the Gram matrices used in defining the independence measures, and incomplete Cholesky decomposition of these matrices. We derive closed-form, efficiently computable approximations for the gradients of these measures, and compare their performance on ICA using both artificial and music data. We show that kernel ICA can scale up to much larger problems than yet attempted, and that incomplete Cholesky decomposition performs better than random sampling.

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 Dates: 2007-08
 Publication Status: Published in print
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 Identifiers: BibTex Citekey: 4192
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Title: Large Scale Kernel Machines
Source Genre: Book
 Creator(s):
Bottou, L, Editor
Chapelle, O1, Editor            
DeCoste, D, Editor
Weston, J, Editor            
Affiliations:
1 Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795            
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 225 - 250 Identifier: ISBN: 0-262-25579-0