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  PAC-Bayesian Generic Chaining

Audibert, J.-Y., & Bousquet, O. (2004). PAC-Bayesian Generic Chaining. In S. Thrun, L. Saul, & B. Schölkopf (Eds.), Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference (pp. 1125-1132). Cambridge, MA, USA: MIT Press.

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 Creators:
Audibert, J-Y, Author
Bousquet, O1, 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: There exist many different generalization error bounds for classification. Each of these bounds contains an improvement over the others for certain situations. Our goal is to combine these different improvements into a single bound. In particular we combine the PAC-Bayes approach introduced by McAllester, which is interesting for averaging classifiers, with the optimal union bound provided by the generic chaining technique developed by Fernique and Talagrand. This combination is quite natural since the generic chaining is based on the notion of majorizing measures, which can be considered as priors on the set of classifiers, and such priors also arise in the PAC-bayesian setting.

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 Dates: 2004-06
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISBN: 0-262-20152-6
URI: http://nips.cc/Conferences/2003/
BibTex Citekey: 2341
 Degree: -

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Title: Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003)
Place of Event: Vancouver, BC, Canada
Start-/End Date: 2003-12-08 - 2003-12-13

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Title: Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference
Source Genre: Proceedings
 Creator(s):
Thrun, S1, Editor
Saul, LK, Editor
Schölkopf, B1, Editor            
Affiliations:
1 Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794            
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1125 - 1132 Identifier: ISBN: 0-262-20152-6