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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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Abstract

We combine Mean Field Annealing 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, MFA at a constant temperature and a stochastic weight penalty technique, known as GENET.

Type: Article
Title: Adapting the energy landscape for MFA
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/79111
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