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), 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].

Item Type: Article
Additional Information: Special issue on Neural Networks for Optimization
Organisations: Electronics & Computer Science
ePrint ID: 259805
Date :
Date Event
November 1995Published
Date Deposited: 23 Aug 2004
Last Modified: 17 Apr 2017 22:23
Further Information:Google Scholar

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