Occam's Razor

Rasmussen, CE; Ghahramani , Z

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Occam's Razor

Rasmussen, C., & Ghahramani, Z. (2001). Occam's Razor. In T. Leen, T. Dietterich, & V. Tresp (Eds.), Advances in Neural Information Processing Systems 13 (pp. 294-300). Cambridge, MA, USA: MIT Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-E2B0-B Version Permalink: https://hdl.handle.net/21.11116/0000-0005-0EE3-C

Genre: Conference Paper

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https://papers.nips.cc/paper/1925-occams-razor.pdf (Publisher version) Open Access status unknown

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Creators:
Rasmussen, CE¹, Author
Ghahramani , Z, Author

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1External Organizations, ou_persistent22

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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: Date issued: 2001-04

Publication Status: Issued

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Identifiers: BibTex Citekey: 2215

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Title: Fourteenth Annual Neural Information Processing Systems Conference (NIPS 2000)

Place of Event: Denver, CO, USA

Start-/End Date: 2000-11-27 - 2000-12-02

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Title: Advances in Neural Information Processing Systems 13

Source Genre: Proceedings

Creator(s):
Leen, TK, Editor
Dietterich, TG, Editor
Tresp, V, Editor

Affiliations:
-

Publ. Info: Cambridge, MA, USA : MIT Press

Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 294 - 300 Identifier: ISBN: 0-262-12241-3