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» Optimizing number of hidden neurons in neural networks
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GECCO
2004
Springer
14 years 1 months ago
Shortcomings with Tree-Structured Edge Encodings for Neural Networks
In evolutionary algorithms a common method for encoding neural networks is to use a tree-structured assembly procedure for constructing them. Since node operators have difficulties...
Gregory Hornby
GECCO
2006
Springer
141views Optimization» more  GECCO 2006»
13 years 11 months ago
Coevolution of neural networks using a layered pareto archive
The Layered Pareto Coevolution Archive (LAPCA) was recently proposed as an effective Coevolutionary Memory (CM) which, under certain assumptions, approximates monotonic progress i...
German A. Monroy, Kenneth O. Stanley, Risto Miikku...
ECML
2007
Springer
14 years 2 months ago
Nondeterministic Discretization of Weights Improves Accuracy of Neural Networks
Abstract. The paper investigates modification of backpropagation algorithm, consisting of discretization of neural network weights after each training cycle. This modification, a...
Marcin Wojnarski
IJCAI
1989
13 years 9 months ago
Training Feedforward Neural Networks Using Genetic Algorithms
Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application ...
David J. Montana, Lawrence Davis
IJCNN
2006
IEEE
14 years 1 months ago
Ensemble of Neural Network Emulations for Climate Model Physics: The Impact on Climate Simulations
—A new application of the NN ensemble approach is presented. It is applied to NN emulations of model physics in complex numerical climate models, and aimed at improving the accur...
Michael S. Fox-Rabinovitz, Vladimir M. Krasnopolsk...