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.