Mining Evolving Learning Algorithms

Author:

Joó András

Publisher

Springer Berlin Heidelberg

Reference18 articles.

1. Langdon, W., Poli, R.: Foundations of Genetic Programming. Springer, Heidelberg (2002)

2. Rattray, M., Saad, D.: Globally optimal on-line learning rules for multi-layer neural networks. Journal of Physics A: Mathematical and General 30(22), L771–L776 (1997)

3. Chalmers, D.J.: The evolution of learning: An experiment in genetic connectionism. In: Touretsky, D.S., Elman, J.L., Sejnowski, T.J., Hinton, G.E. (eds.) Proceedings of the 1990 Connectionist Summer School, pp. 81–90. Morgan Kaufmann, San Francisco (1990)

4. Baxter, J.: The evolution of learning algorithms for artificial neural networks. Complex Systems, 313–326 (1992)

5. Bengio, S., Bengio, Y., Cloutier, J.: Use of genetic programming for the search of a new learning rule for neutral networks. In: Proceedings of the 1994 IEEE World Congress on Computational Intelligence, Orlando, Florida, USA, vol. 1, pp. 324–327. IEEE Press, Los Alamitos (1994)

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