Dynamics of On-Line Gradient Descent Learning for Multilayer Neural Networks

David Saad*, Sara A. Solla

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

24 Scopus citations

Abstract

We consider the problem of on-line gradient descent learning for general two-layer neural networks. An analytic solution is presented and used to investigate the role of the learning rate in controlling the evolution and convergence of the learning process.

Original languageEnglish (US)
Pages302-308
Number of pages7
StatePublished - 1995
Event8th International Conference on Neural Information Processing Systems, NIPS 1995 - Denver, United States
Duration: Nov 27 1995Dec 2 1995

Conference

Conference8th International Conference on Neural Information Processing Systems, NIPS 1995
Country/TerritoryUnited States
CityDenver
Period11/27/9512/2/95

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Signal Processing

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