Discovery of backpropagation learning rules using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@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, backpropagation learning rules, computational method, multilayer network training, supervised learning algorithms, backpropagation, feedforward neural nets, learning (artificial intelligence), multilayer perceptrons",
• 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

Citations