Discovery of backpropagation learning rules using genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{radi:1998:wcci,
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author = "A. Radi and R. Poli",
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title = "Discovery of backpropagation learning rules using
genetic programming",
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booktitle = "Proceedings of the 1998 IEEE World Congress on
Computational Intelligence",
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year = "1998",
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volume = "1",
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pages = "371--375",
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address = "Anchorage",
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month = "4-9 " # may,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming,
backpropagation learning rules, computational method,
multilayer network training, supervised learning
algorithms, backpropagation, feedforward neural nets,
learning (artificial intelligence), multilayer
perceptrons",
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ISBN = "0-7803-4863-X",
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DOI = "doi:10.1109/ICEC.1998.699761",
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abstract = "The backpropagation learning rule is widespread
computational method for training multilayer networks.
Unfortunately, backpropagation suffers from several
problems. The authors have used genetic programming
(GP) to overcome some of these problems and to discover
new supervised learning algorithms. A set of such
learning algorithms has been compared with the standard
backpropagation (SBP) learning algorithm on different
problems and has been shown to provide better
performances. The study indicates that there exist many
supervised learning algorithms better than, but similar
to, SEP and that GP can be used to discover them",
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notes = "ICEC-98 Held In Conjunction With WCCI-98 --- 1998 IEEE
World Congress on Computational Intelligence",
- }
Genetic Programming entries for
Amr Mohamed Mahmoud Khairat Radi
Riccardo Poli
Citations