A Distributed Genetic Algorithm Improving the Generalization Behavior of Neural Networks
Abstract
Artificial neural networks sometimes generalize poorly to unknown inputs, if they have been trained perfectly on relatively small training sets using standard learning algorithms like e.g. backpropagation. In this paper a distributed genetic algorithm is designed and used to improve the network's generalization capabilities by reducing the number of different weights in the neural network.
Cite
Text
Branke et al. "A Distributed Genetic Algorithm Improving the Generalization Behavior of Neural Networks." European Conference on Machine Learning, 1995. doi:10.1007/3-540-59286-5_52Markdown
[Branke et al. "A Distributed Genetic Algorithm Improving the Generalization Behavior of Neural Networks." European Conference on Machine Learning, 1995.](https://mlanthology.org/ecmlpkdd/1995/branke1995ecml-distributed/) doi:10.1007/3-540-59286-5_52BibTeX
@inproceedings{branke1995ecml-distributed,
title = {{A Distributed Genetic Algorithm Improving the Generalization Behavior of Neural Networks}},
author = {Branke, Jürgen and Kohlmorgen, Udo and Schmeck, Hartmut},
booktitle = {European Conference on Machine Learning},
year = {1995},
pages = {107-121},
doi = {10.1007/3-540-59286-5_52},
url = {https://mlanthology.org/ecmlpkdd/1995/branke1995ecml-distributed/}
}