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  The entropy regularization information criterion

Smola, A., Shawe-Taylor, J., Schölkopf, B., & Williamson, R. (2000). The entropy regularization information criterion. Advances in Neural Information Processing Systems 12, 342-348.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-E4CA-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-B5B3-4
Genre: Conference Paper

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http://papers.nips.cc/paper/1677-the-entropy-regularization-information-criterion.pdf (Publisher version)
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 Creators:
Smola, AJ, Author           
Shawe-Taylor, J, Author
Schölkopf, B1, Author           
Williamson, RC, Author
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: Effective methods of capacity control via uniform convergence bounds for function expansions have been largely limited to Support Vector machines, where good bounds are obtainable by the entropy number approach. We extend these methods to systems with expansions in terms of arbitrary (parametrized) basis functions and a wide range of regularization methods covering the whole range of general linear additive models. This is achieved by a data dependent analysis of the eigenvalues of the corresponding design matrix.

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 Dates: 2000-06
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 816
 Degree: -

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Title: Thirteenth Annual Neural Information Processing Systems Conference (NIPS 1999)
Place of Event: Denver, CO, USA
Start-/End Date: 2000-11-29 - 2000-12-04

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Title: Advances in Neural Information Processing Systems 12
Source Genre: Journal
 Creator(s):
Solla, SA, Editor
Leen, TK, Editor
Müller, K, Editor
Affiliations:
-
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 342 - 348 Identifier: ISBN: 0-262-11245-0