Bayesian learning

From Scholarpedia

This article has not been peer-reviewed or accepted for publication yet; It may be unfinished, contain inaccuracies, or unapproved changes.

Author: Dr. David J.C. MacKay, University of Cambridge, UK

While this article is empty, see Bayesian learning on Amazon.

Dr. David J.C. MacKay accepted the invitation on 6 May 2007 (self-imposed deadline: 6 November 2007).

This article will briefly cover: Bayesian learning as a way of describing and deriving both supervised and unsupervised learning algorithms. Supervised learning examples: multi-layer perceptrons. Unsupervised learning examples: clustering, E-M algorithm, Boltzmann machine. Related ideas: 'Score matching'.

Invited by: Dr. Eugene M. Izhikevich, Editor-in-Chief of Scholarpedia, the peer-reviewed open-access encyclopedia
For authors