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

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 Creators:
Schölkopf, B1, 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: 2003-09
 Publication Status: Published online
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 Rev. Method: -
 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: -