A stochastic learning algorithm for generalization problems

C. V. Ramamoorthy, Shashi Shekhar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A discussion is presented of the requirements of learning for generalization, which is NP-complete and cannot be addressed by traditional methods based on gradient descent. The authors present a stochastic learning algorithm based on simulated annealing in weight space and discuss stopping criteria for the algorithm, to avoid overfitting of learning examples.

Original languageEnglish (US)
Title of host publicationTENCON '89
Subtitle of host publicationFourth IEEE Region 10 International Conference
PublisherPubl by IEEE
Pages136-141
Number of pages6
StatePublished - Dec 1 1989
Event4th IEEE Region 10th International Conference - TENCON '89 - Bombay, India
Duration: Nov 22 1989Nov 24 1989

Other

Other4th IEEE Region 10th International Conference - TENCON '89
CityBombay, India
Period11/22/8911/24/89

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