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CORR
2006
Springer
153views Education» more  CORR 2006»
13 years 7 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
EUROGP
2009
Springer
130views Optimization» more  EUROGP 2009»
14 years 2 months ago
One-Class Genetic Programming
One-class classification naturally only provides one-class of exemplars, the target class, from which to construct the classification model. The one-class approach is constructed...
Robert Curry, Malcolm I. Heywood
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
14 years 1 months ago
A developmental model of neural computation using cartesian genetic programming
The brain has long been seen as a powerful analogy from which novel computational techniques could be devised. However, most artificial neural network approaches have ignored the...
Gul Muhammad Khan, Julian F. Miller, David M. Hall...
ICANNGA
2009
Springer
203views Algorithms» more  ICANNGA 2009»
14 years 2 months ago
NEAT in HyperNEAT Substituted with Genetic Programming
In this paper we present application of genetic programming (GP) [1] to evolution of indirect encoding of neural network weights. We compare usage of original HyperNEAT algorithm w...
Zdenek Buk, Jan Koutník, Miroslav Snorek
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
14 years 1 months ago
Best SubTree genetic programming
The result of the program encoded into a Genetic Programming (GP) tree is usually returned by the root of that tree. However, this is not a general strategy. In this paper we pres...
Oana Muntean, Laura Diosan, Mihai Oltean