Adapting the Energy Landscape for MFA


Burge, P. and Shawe-Taylor, J. (1995) Adapting the Energy Landscape for MFA. Journal of Artificial Neural Networks, 2, (4), 449-454.

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Description/Abstract

We combine Mean Field Annealing (MFA) [7] with an anti-hebbian type adaptive weight penalty method forming an algorithm that performs well on standard benchmark optimization problems. We compare the hybrid algorithm with the Petford and Welsh algorithm [5], MFA at a constant temperature[7] and a stochastic weight penalty technique, known as GENET, proposed by Tsang & Wang (1992) [8].

Item Type: Article
Additional Information: Special issue on Neural Networks for Optimization
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science
ePrint ID: 259805
Date Deposited: 23 Aug 2004
Last Modified: 27 Mar 2014 20:02
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/259805

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