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  Sampling Techniques for Kernel Methods

Achlioptas, D., McSherry, F., & Schölkopf, B. (2002). Sampling Techniques for Kernel Methods. Advances in Neural Information Processing Systems, 335-342.

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 Creators:
Achlioptas, D, Author
McSherry, F, Author
Schölkopf, B1, Author           
Dietterich, Editor
T.G., Editor
Becker, S., Editor
Ghahramani, Z., Editor
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Abstract: We propose randomized techniques for speeding up Kernel Principal Component Analysis on three levels: sampling and quantization of the Gram matrix in training, randomized rounding in evaluating the kernel expansions, and random projections in evaluating the kernel itself. In all three cases, we give sharp bounds on the accuracy of the obtained approximations.

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 Dates: 2002-09
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISBN: 0-262-04208-8
URI: http://books.nips.cc/nips14.html
BibTex Citekey: 1856
 Degree: -

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Title: Fifteenth Annual Neural Information Processing Systems Conference (NIPS 2001)
Place of Event: Vancouver, BC, Canada
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Title: Advances in Neural Information Processing Systems
Source Genre: Journal
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Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 335 - 342 Identifier: -