Biased learning in Boolean perceptrons

The generalization ability of Hebbian Boolean perceptrons can be improved by a kind of feedback mechanism in which the student net judges the difficulty of a new example from its previous experience. It is shown that by giving a higher weight to the hard examples both generalization and learning abilities can be increased. Analytical as well as numerical results are presented for both cases where the examples are drawn at random or selected in an intelligent form.

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Year of publication:	1992
Authors:	Kinouchi, Osame ; Caticha, Nestor
Published in:	Physica A: Statistical Mechanics and its Applications. - Elsevier, ISSN 0378-4371. - Vol. 185.1992, 1, p. 411-416
Publisher:	Elsevier

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010587160