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A practical Monte Carlo implementation of Bayesian learning


Conference Paper


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.

Author(s): Rasmussen, CE.
Book Title: Advances in Neural Information Processing Systems 8
Journal: Advances in Neural Processing Systems 8
Pages: 598-604
Year: 1996
Month: June
Day: 0
Editors: Touretzky, D.S. , M.C. Mozer, M.E. Hasselmo
Publisher: MIT Press

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

Event Name: Ninth Annual Conference on Neural Information Processing Systems (NIPS 1995)
Event Place: Denver, CO, USA

Address: Cambridge, MA, USA
Digital: 0
ISBN: 0-262-20107-0
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF


  title = {A practical Monte Carlo implementation of Bayesian
  author = {Rasmussen, CE.},
  journal = {Advances in Neural Processing Systems 8},
  booktitle = {Advances in Neural Information Processing Systems 8},
  pages = {598-604},
  editors = {Touretzky, D.S. , M.C. Mozer, M.E. Hasselmo},
  publisher = {MIT Press},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Cambridge, MA, USA},
  month = jun,
  year = {1996},
  month_numeric = {6}