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  Semi-supervised kernel regression using whitened function classes

Franz, M., Kwon, Y., Rasmussen, C., & Schölkopf, B. (2004). Semi-supervised kernel regression using whitened function classes. In C. Rasmussen, H. Bülthoff, B. Schölkopf, & M. Giese (Eds.), Pattern Recognition: 26th DAGM Symposium, Tübingen, Germany, August 30 - September 1, 2004 (pp. 18-26). Berlin, Germany: Springer.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-F37A-B Version Permalink: http://hdl.handle.net/21.11116/0000-0005-5260-2
Genre: Conference Paper

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 Creators:
Franz, MO1, 2, Author              
Kwon, Y1, 2, Author              
Rasmussen, CE1, 2, Author              
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, ou_1497794              

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 Abstract: The use of non-orthonormal basis functions in ridge regression leads to an often undesired non-isotropic prior in function space. In this study, we investigate an alternative regularization technique that results in an implicit whitening of the basis functions by penalizing directions in function space with a large prior variance. The regularization term is computed from unlabelled input data that characterizes the input distribution. Tests on two datasets using polynomial basis functions showed an improved average performance compared to standard ridge regression.

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 Dates: 2004-09
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 2638
 Degree: -

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Title: 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004)
Place of Event: Tübingen, Germany
Start-/End Date: 2004-08-30 - 2004-09-01

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Title: Pattern Recognition: 26th DAGM Symposium, Tübingen, Germany, August 30 - September 1, 2004
Source Genre: Proceedings
 Creator(s):
Rasmussen, CE1, Editor            
Bülthoff, H1, Editor            
Schölkopf, B1, Editor            
Giese, MA, Editor            
Affiliations:
1 Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794            
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 18 - 26 Identifier: ISBN: 978-3-540-22945-2

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Publ. Info: -
Pages: - Volume / Issue: 3175 Sequence Number: - Start / End Page: - Identifier: -