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  Kernel principal component analysis

Schölkopf, B., Smola, A., & Müller, K.-R. (1999). Kernel principal component analysis. In B. Schölkopf, C. Burges, & A. Smola (Eds.), Advances in kernel methods: support vector learning (pp. 327-352). Cambridge, MA, USA: MIT Press.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-E775-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-C48E-E
Genre: Conference Paper

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Locator:
https://dl.acm.org/doi/10.5555/299094.299113 (Publisher version)
Description:
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 Creators:
Schölkopf, B1, 2, Author              
Smola, AJ, Author              
Müller, K-R, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Dates: 1999-02
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 789
DOI: 10.5555/299094.299113
 Degree: -

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Title: Eleventh Annual Conference on Neural Information Processing (NIPS 1997)
Place of Event: Breckenridge, CO, USA
Start-/End Date: 1997-12-01 - 1997-12-06

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Title: Advances in kernel methods: support vector learning
Source Genre: Proceedings
 Creator(s):
Schölkopf, B1, Editor            
Burges, CJC, Editor
Smola, AJ, Editor            
Affiliations:
1 Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794            
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: 376 Volume / Issue: - Sequence Number: - Start / End Page: 327 - 352 Identifier: ISBN: 0-262-19416-3