Developments in Probabilistic Modelling with Neural Networks---Ensemble Learning

David J C MacKay

Ensemble learning by variational free energy minimization is a framework for statistical inference in which an ensemble of parameter vectors is optimized rather than a single parameter vector. The ensemble approximates the posterior probability distribution of the parameters. In this paper I give a review of ensemble learning using a simple example.

postscript.

@INPROCEEDINGS{MacKay95:snn,
 KEY		="MacKay",
 AUTHOR		="D. J. C. MacKay",
 TITLE		="Developments in Probabilistic Modelling with Neural
		 Networks -- Ensemble Learning",
 BOOKTITLE	="Neural Networks: Artificial Intelligence and
		 Industrial Applications. Proceedings of the 3rd
		 Annual Symposium on Neural Networks, Nijmegen,
		 Netherlands, 14-15 September 1995",
 YEAR		="1995",
 PUBLISHER	="Springer", 
 editors="Kappen, B. and Gielen, S.",
 ADDRESS	="Berlin",
 PAGES		="191-198", annote={MRAO 1926}
}

David MacKay's: home page, publications. bibtex file.