A practical Monte Carlo implementation of Bayesian learning

Rasmussen, CE

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A practical Monte Carlo implementation of Bayesian learning

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https://papers.nips.cc/paper/1029-a-practical-monte-carlo-implementation-of-bayesian-learning.pdf
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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.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-EB64-D

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.