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Functional Optimisation of Online Algorithms in Multilayer Neural Networks

Renato Vicente·Nestor Caticha
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Abstract

We study the online dynamics of learning in fully connected soft committee machines in the student-teacher scenario. The locally optimal modulation function, which determines the learning algorithm, is obtained from a variational argument in such a manner as to maximise the average generalisation error decay per example. Simulations results for the resulting algorithm are presented for a few cases. The symmetric phase plateaux are found to be vastly reduced in comparison to those found when online backpropagation algorithms are used. A discussion of the implementation of these ideas as practical algorithms is given.

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Renato Vicente, Nestor Caticha. 1997-06-02. Functional Optimisation of Online Algorithms in Multilayer Neural Networks. https://doi.org/10.1088/0305-4470%2F30%2F17%2F002

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