Discovering efficient learning rules for feedforward neural networks using genetic programming
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- @InCollection{radi:2003:RAIPA,
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author = "Amr Radi and Riccardo Poli",
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title = "Discovering efficient learning rules for feedforward
neural networks using genetic programming",
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booktitle = "Recent advances in intelligent paradigms and
applications",
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year = "2003",
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ISBN = "3-7908-1538-1",
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pages = "133--159",
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publisher = "Physica-Verlag GmbH",
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address = "Heidelberg, Germany, Germany",
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editor = "Ajith Abraham and Lakhmi Jain and Janusz Kacprzyk",
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chapter = "7",
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keywords = "genetic algorithms, genetic programming, ANN",
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URL = "http://www.springer.com/computer/ai/book/978-3-7908-1538-2",
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abstract = "The Standard BackPropagation (SBP) algorithm is the
most widely known and used learning method for training
neural networks. Unfortunately, SBP suffers from
several problems such as sensitivity to the initial
conditions and very slow convergence. Here we describe
how we used Genetic Programming, a search algorithm
inspired by Darwinian evolution, to discover new
supervised learning algorithms for neural networks
which can overcome some of these problems. Comparing
our new algorithms with SBP on different problems we
show that these are faster, are more stable and have
greater feature extracting capabilities.",
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notes = "See also \cite{radi:2002:CSM360}",
- }
Genetic Programming entries for
Amr Mohamed Mahmoud Khairat Radi
Riccardo Poli
Citations