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  Occam's Razor

Rasmussen, C. (2001). Occam's Razor. Advances in Neural Information Processing Systems 13, 294-300.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-E2B0-B Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-E2B1-9
Genre: Conference Paper

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 Creators:
Rasmussen, CE1, Author              
Leen, Editor
T.K., Editor
Dietterich, T.G., Editor
Tresp, V., Editor
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, escidoc:1497795              

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 Abstract: The Bayesian paradigm apparently only sometimes gives rise to Occam's Razor; at other times very large models perform well. We give simple examples of both kinds of behaviour. The two views are reconciled when measuring complexity of functions, rather than of the machinery used to implement them. We analyze the complexity of functions for some linear in the parameter models that are equivalent to Gaussian Processes, and always find Occam's Razor at work.

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 Dates: 2001-04
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: ISBN: 0-262-12241-3
URI: http://books.nips.cc/nips13.html
BibTex Citekey: 2215
 Degree: -

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Title: Fourteenth Annual Neural Information Processing Systems Conference (NIPS 2000)
Place of Event: Denver, CO, USA
Start-/End Date: -

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Title: Advances in Neural Information Processing Systems 13
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 294 - 300 Identifier: -