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GECCO
2009
Springer
130views Optimization» more  GECCO 2009»
14 years 10 days ago
Neutrality and variability: two sides of evolvability in linear genetic programming
The notion of evolvability has been put forward to describe the“core mechanism”of natural and artificial evolution. Recently, studies have revealed the influence of the envi...
Ting Hu, Wolfgang Banzhaf
CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 7 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
CEC
2010
IEEE
13 years 5 months ago
Active Learning Genetic programming for record deduplication
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...
Junio de Freitas, Gisele L. Pappa, Altigran Soares...
CEC
2009
IEEE
14 years 2 months ago
Optimization of the sizing of a solar thermal electricity plant: Mathematical programming versus genetic algorithms
— Genetic algorithms (GAs) have been argued to constitute a flexible search thereby enabling to solve difficult problems which classical optimization methodologies may find ha...
Jose M. Cabello, Jose M. Cejudo, Mariano Luque, Fr...
BMCBI
2006
144views more  BMCBI 2006»
13 years 7 months ago
ProFAT: a web-based tool for the functional annotation of protein sequences
Background: The functional annotation of proteins relies on published information concerning their close and remote homologues in sequence databases. Evidence for remote sequence ...
Charles Richard Bradshaw, Vineeth Surendranath, Bi...