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Proceedings Paper

Alternative method for the connectionist learning of k-DNF expressions
Author(s): Thomas Bitterman
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Paper Abstract

We show that the extremely long learning times imposed upon connectionist systems by the use of general learning methods such as back propagation and simulated annealing can be drastically shortened by the use of methods geared toward the problem at hand. In particular, the learning of k-DNF expressions is analyzed and a new, more efficient, algorithm is proposed.

Paper Details

Date Published: 1 July 1992
PDF: 6 pages
Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140102
Show Author Affiliations
Thomas Bitterman, Louisiana State Univ. (United States)

Published in SPIE Proceedings Vol. 1710:
Science of Artificial Neural Networks
Dennis W. Ruck, Editor(s)

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