# A Mean Field Theory Learning Algorithm for N eu ral N etwor ks

@inproceedings{Peterson2006AMF, title={A Mean Field Theory Learning Algorithm for N eu ral N etwor ks}, author={C. Peterson and James R. Anderson}, year={2006} }

Based on t he Boltzmann Machine concept, we derive a lear ning algorith m in which time-consuming stochastic measurements of correlations a re replaced by solutions to dete rminist ic mean field theory equ ations. T he method is applied to t he XOR (exclusive-or ), encoder, and line sym metry problems with substantial success. We observe speedup facto rs ranging from 10 to 30 for these ap plicat ions and a significantly bet ter learning perform an ce in general. 1. Motivation and results 1.1… Expand

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