Saad, David and Rattray, Magnus (1997). Globally optimal parameters for on-line learning in multilayer neural networks. Physical Review Letters, 79 (13), pp. 2578-2581.
Abstract
We present a framework for calculating globally optimal parameters, within a given time frame, for on-line learning in multilayer neural networks. We demonstrate the capability of this method by computing optimal learning rates in typical learning scenarios. A similar treatment allows one to determine the relevance of related training algorithms based on modifications to the basic gradient descent rule as well as to compare different training methods.
Divisions: | College of Engineering & Physical Sciences > Systems analytics research institute (SARI) |
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Additional Information: | Copyright of the American Physical Society |
Publication ISSN: | 1079-7114 |
Last Modified: | 29 Nov 2023 10:00 |
Date Deposited: | 11 Mar 2019 17:28 |
Full Text Link: |
10.1103/PhysRevLett.79.2578 |
Related URLs: |
http://www.scop ... tnerID=8YFLogxK
(Scopus URL) http://prola.ap ... v79/i13/p2578_1 (Publisher URL) |
PURE Output Type: | Article |
Published Date: | 1997-09-29 |
Authors: |
Saad, David
Rattray, Magnus |