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» Evolutionary learning of small networks
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GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
15 years 3 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
JMLR
2012
13 years 2 months ago
Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
Marco Grzegorczyk, Dirk Husmeier
ESANN
2007
15 years 1 months ago
Systematicity in sentence processing with a recursive self-organizing neural network
Abstract. As potential candidates for human cognition, connectionist models of sentence processing must learn to behave systematically by generalizing from a small traning set. It ...
Igor Farkas, Matthew W. Crocker
ECAL
1999
Springer
15 years 4 months ago
Evolution of Neural Controllers with Adaptive Synapses and Compact Genetic Encoding
Abstract. This paper is concerned with arti cial evolution of neurocontrollers with adaptive synapses for autonomous mobile robots. The method consists of encoding on the genotype ...
Dario Floreano, Joseba Urzelai
ICANN
2009
Springer
15 years 4 months ago
Scalable Neural Networks for Board Games
Learning to solve small instances of a problem should help in solving large instances. Unfortunately, most neural network architectures do not exhibit this form of scalability. Our...
Tom Schaul, Jürgen Schmidhuber