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» Unsupervised Problem Decomposition Using Genetic Programming
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EUROGP
2007
Springer
126views Optimization» more  EUROGP 2007»
14 years 2 months ago
Training Binary GP Classifiers Efficiently: A Pareto-coevolutionary Approach
The conversion and extension of the Incremental Pareto-Coevolution Archive algorithm (IPCA) into the domain of Genetic Programming classification is presented. In particular, the ...
Michal Lemczyk, Malcolm I. Heywood
ICTAI
2009
IEEE
14 years 5 months ago
Evolution Strategies for Constants Optimization in Genetic Programming
Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
César Luis Alonso, José Luis Monta&n...
GECCO
2005
Springer
189views Optimization» more  GECCO 2005»
14 years 4 months ago
Molecular programming: evolving genetic programs in a test tube
We present a molecular computing algorithm for evolving DNA-encoded genetic programs in a test tube. The use of synthetic DNA molecules combined with biochemical techniques for va...
Byoung-Tak Zhang, Ha-Young Jang
GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
14 years 5 months ago
Unwitting distributed genetic programming via asynchronous JavaScript and XML
The success of a genetic programming system in solving a problem is often a function of the available computational resources. For many problems, the larger the population size an...
Jon Klein, Lee Spector
HAIS
2009
Springer
14 years 3 months ago
Unsupervised Feature Selection in High Dimensional Spaces and Uncertainty
Developing models and methods to manage data vagueness is a current effervescent research field. Some work has been done with supervised problems but unsupervised problems and unce...
José Ramón Villar, María del ...