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  Multivariate Regression via Stiefel Manifold Constraints

BakIr, G., Gretton, A., Franz, M., & Schölkopf, B. (2004). Multivariate Regression via Stiefel Manifold Constraints. In C. Rasmussen, H. Bülthoff, B. Schölkopf, & M. Giese (Eds.), Pattern Recognition: 26th DAGM Symposium, Tübingen, Germany, August 30 - September 1, 2004 (pp. 262-269). Berlin, Germany: Springer.

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 Creators:
BakIr, G1, 2, Author           
Gretton, A1, 2, Author           
Franz, M1, 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, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: We introduce a learning technique for regression between high-dimensional spaces. Standard methods typically reduce this task to many one-dimensional problems, with each output dimension considered independently. By contrast, in our approach the feature construction and the regression estimation are performed jointly, directly minimizing a loss function that we specify, subject to a rank constraint. A major advantage of this approach is that the loss is no longer chosen according to the algorithmic requirements, but can be tailored to the characteristics of the task at hand; the features will then be optimal with respect to this objective, and dependence between the outputs can be exploited.

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 Dates: 2004-09
 Publication Status: Published in print
 Pages: -
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 Rev. Type: -
 Identifiers: BibTex Citekey: 2845
DOI: 10.1007/978-3-540-28649-3_32
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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, HH1, 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: 262 - 269 Identifier: ISBN: 978-3-540-22945-2

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