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  Adapting Codes and Embeddings for Polychotomies

Rätsch, G., Smola, A., & Mika, S. (2003). Adapting Codes and Embeddings for Polychotomies. Advances in Neural Information Processing Systems, 513-520.

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 Creators:
Rätsch, G1, Author           
Smola, A, Author
Mika, S, Author
Becker, Editor
S., Editor
Thrun, S., Editor
Obermayer, K., Editor
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Abstract: In this paper we consider formulations of multi-class problems based on a generalized notion of a margin and using output coding. This includes, but is not restricted to, standard multi-class SVM formulations. Differently from many previous approaches we learn the code as well as the embedding function. We illustrate how this can lead to a formulation that allows for solving a wider range of problems with for instance many classes or even “missing classes”. To keep our optimization problems tractable we propose an algorithm capable of solving them using twoclass classifiers, similar in spirit to Boosting.

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 Dates: 2003-10
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISBN: 0-262-02550-7
URI: http://books.nips.cc/nips15.html
BibTex Citekey: 2183
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Title: Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002)
Place of Event: Vancouver, BC, Canada
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Title: Advances in Neural Information Processing Systems
Source Genre: Journal
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Affiliations:
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 513 - 520 Identifier: -