Genetic Programming Discovers Efficient Learning Rules for the Hidden and Output Layers of Feedforward Neural Networks
Created by W.Langdon from
gp-bibliography.bib Revision:1.7975
- @TechReport{radi:CSRP-98-15,
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author = "Amr M. Radi and Riccardo Poli",
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title = "Genetic Programming Discovers Efficient Learning Rules
for the Hidden and Output Layers of Feedforward Neural
Networks",
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institution = "University of Birmingham, School of Computer Science",
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number = "CSRP-98-15",
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month = dec,
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year = "1998",
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file = "/1998/CSRP-98-15.ps.gz",
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URL = "ftp://ftp.cs.bham.ac.uk/pub/tech-reports/1998/CSRP-98-15.ps.gz",
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reportfilename = "pub/tech-reports/1998/CSRP-98-15.ps.gz",
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keywords = "genetic algorithms, genetic programming",
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abstract = "The learning method is critical for obtaining good
generalisation in neural networks with limited training
data. The Standard BackPropagation (SBP) training
algorithm suffers from several problems such as
sensitivity to the initial conditions and very slow
convergence. The aim of this work is to use Genetic
Programming (GP) to discover new supervised learning
algorithms which can overcome some of these problems.
In previous research a new learning algorithms for the
output layer has been discovered using GP. By comparing
this with SBP on different problems better performance
was demonstrated. This paper shows that GP can also
discover better learning algorithms for the hidden
layers to be used in conjunction with the algorithm
previously discovered. Comparing these with SBP on
different problems we show they provide better
performances. This study indicates that there exist
many supervised learning algorithms better than SBP and
that GP can be used to discover them.",
- }
Genetic Programming entries for
Amr Mohamed Mahmoud Khairat Radi
Riccardo Poli
Citations