%0 Conference Paper %1 radi:1999:EDLRFNNSAF %A Radi, Amr %A Poli, Riccardo %B Proceedings of the Genetic and Evolutionary Computation Conference %C Orlando, Florida, USA %D 1999 %E Banzhaf, Wolfgang %E Daida, Jason %E Eiben, Agoston E. %E Garzon, Max H. %E Honavar, Vasant %E Jakiela, Mark %E Smith, Robert E. %I Morgan Kaufmann %K algorithms, and evolvable genetic hardware programming %P 1178--1183 %T Evolutionary Discovery of Learning Rules for Feedforward Neural Networks with Step Activation Function %U http://www.cs.bham.ac.uk/~wbl/biblio/gecco1999/GP-428.attempt2.ps %V 2 %X Neural networks with step activation function can be very efficient ways of performing non linear mappings. However, no standard learning algorithm exists for training this kind of neural networks. In this work we use Genetic Programming (GP) to discover supervised learning algorithms which can train neural networks with step activation function. Thanks to GP, a new learning algorithm has been discovered which has been shown to provide good performance. %@ 1-55860-611-4

@inproceedings{radi:1999:EDLRFNNSAF, abstract = {Neural networks with step activation function can be very efficient ways of performing non linear mappings. However, no standard learning algorithm exists for training this kind of neural networks. In this work we use Genetic Programming (GP) to discover supervised learning algorithms which can train neural networks with step activation function. Thanks to GP, a new learning algorithm has been discovered which has been shown to provide good performance.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Orlando, Florida, USA}, author = {Radi, Amr and Poli, Riccardo}, biburl = {https://www.bibsonomy.org/bibtex/2c9ddc169f30f95f9a498f5b2366ed5e3/brazovayeye}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference}, editor = {Banzhaf, Wolfgang and Daida, Jason and Eiben, Agoston E. and Garzon, Max H. and Honavar, Vasant and Jakiela, Mark and Smith, Robert E.}, interhash = {4402d2311997dd34232a39293cdeb680}, intrahash = {c9ddc169f30f95f9a498f5b2366ed5e3}, isbn = {1-55860-611-4}, keywords = {algorithms, and evolvable genetic hardware programming}, month = {13-17 July}, notes = {GECCO-99 A joint meeting of the eighth international conference on genetic algorithms (ICGA-99) and the fourth annual genetic programming conference (GP-99)}, pages = {1178--1183}, publisher = {Morgan Kaufmann}, publisher_address = {San Francisco, CA 94104, USA}, timestamp = {2008-06-19T17:50:01.000+0200}, title = {Evolutionary Discovery of Learning Rules for Feedforward Neural Networks with Step Activation Function}, url = {http://www.cs.bham.ac.uk/~wbl/biblio/gecco1999/GP-428.attempt2.ps}, volume = 2, year = 1999 }