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Mean field annealing

From Wikipedia, the free encyclopedia

Mean field annealing is a deterministic approximation to the simulated annealing technique of solving optimization problems.[1] This method uses mean field theory and is based on Peierls' inequality.

References

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  1. ^ Bilbro, G.L.; Snyder, W.E.; Garnier, S.J.; Gault, J.W. (Jan 1992). "Mean field annealing: a formalism for constructing GNC-like algorithms" (PDF). IEEE Transactions on Neural Networks. 3 (1): 131–138. doi:10.1109/72.105426. PMID 18276414.