Discovery of backpropagation learning rules using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{radi:1998:wcci,
  author =       "A. Radi and R. Poli",
  title =        "Discovery of backpropagation learning rules using
                 genetic programming",
  booktitle =    "Proceedings of the 1998 IEEE World Congress on
                 Computational Intelligence",
  year =         "1998",
  volume =       "1",
  pages =        "371--375",
  address =      "Anchorage",
  month =        "4-9 " # may,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7803-4863-X",
  doi =          "doi:10.1109/ICEC.1998.699761",
  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",
  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