LETTER TO THE EDITOR Globally optimal on-line learning rules for multi-layer neural networks
نویسندگان
چکیده
We present a method for determining the globally optimal on-line learning rule for a soft committee machine under a statistical mechanics framework. This rule maximizes the total reduction in generalization error over the whole learning process. A simple example demonstrates that the locally optimal rule, which maximizes the rate of decrease in generalization error, may perform poorly in comparison.
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