Kernel principal component analysis

Schölkopf, B; Smola, AJ; Müller, K-R

doi:10.5555/299094.299113

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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: https://hdl.handle.net/11858/00-001M-0000-0013-E775-3 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-C48E-E

Genre: Conference Paper

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https://dl.acm.org/doi/10.5555/299094.299113 (Publisher version) Open Access status unknown

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Creators:
Schölkopf, B^{1, 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: Date issued: 1999-02

Publication Status: Issued

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Identifiers: BibTex Citekey: 789
DOI: 10.5555/299094.299113

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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