Kernel methods and dimensionality reduction

Schölkopf, B

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Kernel methods and dimensionality reduction

Schölkopf, B. (2003). Kernel methods and dimensionality reduction. Talk presented at Designing Tomorrow' s Category-Level 3D Object Recognition Systems: An International Workshop. Taormina, Italy. 2003-09-08.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-DE1A-D Version Permalink: https://hdl.handle.net/21.11116/0000-0005-7EDD-6

Genre: Talk

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http://lear.inrialpes.fr/people/schmid/sicile/wreport.pdf (Abstract) Open Access status unknown

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Creators:
Schölkopf, B^{1, 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: The talk will start with a short tutorial on kernel methods
in machine learning. Following this, we will describe how some recent methods for nonlinear dimensionality reduction can be
viewed as kernel methods.

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Dates: Published Online: 2003-09

Publication Status: Published online

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Identifiers: BibTex Citekey: 2412

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Title: Designing Tomorrow' s Category-Level 3D Object Recognition Systems: An International Workshop

Place of Event: Taormina, Italy

Start-/End Date: 2003-09-08

Invited: Yes

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Title: Designing Tomorrow' s Category-Level 3D Object Recognition Systems: An International Workshop

Source Genre: Proceedings

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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 13 - 14 Identifier: -