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  A practical Monte Carlo implementation of Bayesian learning

Rasmussen, C. (1996). A practical Monte Carlo implementation of Bayesian learning. In D. Touretzky, M. Mozer, & M. Hasselmo (Eds.), Advances in Neural Processing Systems 8 (pp. 598-604). Cambridge, MA, USA: MIT Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-EB64-D Version Permalink: https://hdl.handle.net/21.11116/0000-0002-DE83-0
Genre: Conference Paper

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 Creators:
Rasmussen, CE1, Author           
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: A practical method for Bayesian training of feed-forward neural networks using sophisticated Monte Carlo methods is presented and evaluated. In reasonably small amounts of computer time this approach outperforms other state-of-the-art methods on 5 datalimited tasks from real world domains.

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 Dates: 1996-06
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: BibTex Citekey: 2999
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Title: Ninth Annual Conference on Neural Information Processing Systems (NIPS 1995)
Place of Event: Denver, CO, USA
Start-/End Date: 1995-11-27 - 1995-12-02

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Title: Advances in Neural Processing Systems 8
Source Genre: Proceedings
 Creator(s):
Touretzky , DS, Editor
Mozer, MC, Editor
Hasselmo, ME, Editor
Affiliations:
-
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 598 - 604 Identifier: ISBN: 0-262-20107-0