A Class of Asymptotically Stable Algorithms for Learning-Rate Adaptation

Rüger, Stefan (1998). A Class of Asymptotically Stable Algorithms for Learning-Rate Adaptation. Algorithmica, 22(1-2) pp. 198–210.

DOI (Digital Object Identifier) Link:	http://dx.doi.org/10.1007/PL00013830

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Abstract

A stability criterion for learning is given. In the case of learning-rate adaptation of backpropagation, a class of asymptotically stable algorithms is presented and studied, including a convergence proof. Simulations demonstrate relevance and limitations.

Item Type:	Journal Article
ISSN:	0178-4617
Academic Unit/Department:	Knowledge Media Institute
Item ID:	11955
Depositing User:	Users 8580 not found.
Date Deposited:	08 Oct 2008 13:13
Last Modified:	04 Apr 2011 09:23
URI:	http://oro.open.ac.uk/id/eprint/11955

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