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Regularization and Complexity Control in Feed-forward Networks

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Original languageEnglish
Title of host publicationProceedings International Conference on Artificial Neural Networks ICANN'95
EditorsF. Fougelman-Soulie, P. Gallinari
Pages141–148
Number of pages8
Volume1
Publication statusPublished - 1995

Abstract

In this paper we consider four alternative approaches to complexity control in feed-forward networks based respectively on architecture selection, regularization, early stopping, and training with noise. We show that there are close similarities between these approaches and we argue that, for most practical applications, the technique of regularization should be the method of choice.

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