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Adapting the Energy Landscape for MFA

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

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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]

Type: Article
Title: Adapting the Energy Landscape for MFA
Additional information: Special issue on Neural Networks for Optimization
Keywords: optimization
UCL classification: UCL > School of BEAMS
UCL > School of BEAMS > Faculty of Engineering Science
URI: http://discovery.ucl.ac.uk/id/eprint/79111
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