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A Meta Neural Network Polling System for the RPROP Learning Rule

  • C. McCormack
Conference paper

Abstract

This paper proposes an application independent method of automating learning rule parameter selection using a group of supervisor neural networks, known as meta neural networks, to alter the value of a learning rule parameter during training. Each meta neural network is trained using data generated by observing the training of a neural network and recording the effects of the selection of various parameter values. A group of meta neural networks is then polled to obtain a parameter value for a learning rule. Experiments are undertaken to see how this method performs by using it to adapt a global parameter of RPROP.

Keywords

Learning Rule Heart Problem Rule Parameter Supervisor Neural Network Thyroid Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    C. McCormack. A study of the adaptation of learning rule parameters using a meta neural network. In 13th European Meeting on Systems and Cybernetic Research, volume 2, pages 1043–1048, 1996.Google Scholar
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    C. McCormack. Using a meta neural network for RPROP parameter adaptation. In Proc. European Symposium on Artificial Neural Networks, pages 7–12, 1996.Google Scholar
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    I. Pitas. Parallel Algorithms for Digital Image Processing, Vision and Neural Networks. John Wiley and Sons, Chichester, 1993.Google Scholar
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    L. Prechelt. PROBEN1: A set of neural network benchmarking rules. Technical Report 21/94, Dept. of Informatics, University of Karlsruhe, Germany, 1994. ftp://ftp.ira.uka.de/pub/neuron/probenl.tar.gz.Google Scholar
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    M. Riedmiller. Advanced supervised learning in multilayered perceptrons: Prom backpropagation to adaptive learning algorithms. Computer Standards and Interfaces, 16:265–278, 1994.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 1998

Authors and Affiliations

  • C. McCormack
    • 1
  1. 1.Department of Computer ScienceUniversity College CorkCorkIreland

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