Efficient block training of multilayer perceptrons.

A Navia-Vázquez; A R Figueiras-Vidal

doi:10.1162/089976600300015448

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Efficient block training of multilayer perceptrons.

A Navia-Vázquez·A R Figueiras-Vidal

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Abstract

The attractive possibility of applying layerwise block training algorithms to multilayer perceptrons MLP, which offers initial advantages in computational effort, is refined in this article by means of introducing a sensitivity correction factor in the formulation. This results in a clear performance advantage, which we verify in several applications. The reasons for this advantage are discussed and related to implicit relations with second-order techniques, natural gradient formulations through Fisher's information matrix, and sample selection. Extensions to recurrent networks and other research lines are suggested at the close of the article.

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Algorithms Expert Systems Humans Learning Neoplasms Neural Networks, Computer Journal Article Research Support, Non-U.S. Gov't

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A Navia-Vázquez, A R Figueiras-Vidal. 2000. Efficient block training of multilayer perceptrons.. https://doi.org/10.1162/089976600300015448

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