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» Evolutionary Optimization of RBF Networks
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GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
13 years 11 months ago
The baldwin effect in developing neural networks
The Baldwin Effect is a very plausible, but unproven, biological theory concerning the power of learning to accelerate evolution. Simple computational models in the 1980’s gave...
Keith L. Downing
GECCO
2008
Springer
116views Optimization» more  GECCO 2008»
13 years 9 months ago
Stock trading strategies by genetic network programming with flag nodes
Genetic Network Programming (GNP) has been proposed as a graph-based evolutionary algorithm. GNP works well especially in dynamic environments due to its graph structures. In addi...
Shingo Mabu, Yan Chen, Etsushi Ohkawa, Kotaro Hira...
IJON
2007
118views more  IJON 2007»
13 years 7 months ago
Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm
To predict the 100 missing values from a time series of 5000 data points, given for the IJCNN 2004 time series prediction competition, recurrent neural networks (RNNs) are trained...
Xindi Cai, Nian Zhang, Ganesh K. Venayagamoorthy, ...
NECO
2007
115views more  NECO 2007»
13 years 7 months ago
Training Recurrent Networks by Evolino
In recent years, gradient-based LSTM recurrent neural networks (RNNs) solved many previously RNN-unlearnable tasks. Sometimes, however, gradient information is of little use for t...
Jürgen Schmidhuber, Daan Wierstra, Matteo Gag...
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
14 years 2 months ago
Robust multi-cellular developmental design
This paper introduces a continuous model for Multi-cellular Developmental Design. The cells are fixed on a 2D grid and exchange ”chemicals” with their neighbors during the gr...
Alexandre Devert, Nicolas Bredeche, Marc Schoenaue...