A Mean Eld Algorithm for Bayes Learning in Large Feed-forward Neural Networks
We present a mean eld algorithm to realise Bayes optimal predictions in large feed-forward networks. The derivation of the algorithm is based on methods developed within statistical mechanics of disordered systems. The algorithm also provides a leave-one-out cross-validation test of the predictions. Simulations show excellent agreement with theoretical results of statistical mechanics. Furthermore we derive other simpler mean eld algorithms and make a comparison study.