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GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
14 years 2 months ago
Evolving kernels for support vector machine classification
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
Keith Sullivan, Sean Luke
GECCO
2000
Springer
225views Optimization» more  GECCO 2000»
14 years 1 months ago
Solving Large Binary Quadratic Programming Problems by Effective Genetic Local Search Algorithm
A genetic local search (GLS) algorithm, which is a combination technique of genetic algorithm and local search, for the unconstrained binary quadratic programming problem (BQP) is...
Kengo Katayama, Masafumi Tani, Hiroyuki Narihisa
ENGL
2007
121views more  ENGL 2007»
13 years 10 months ago
A Comparison between Genetic Algorithms and Evolutionary Programming based on Cutting Stock Problem
—Genetic Algorithms (GA) and Evolutionary Programming (EP) are two well-known optimization methods that belong to the class of Evolutionary Algorithms (EA). Both methods have gen...
Raymond Chiong, Ooi Koon Beng
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
13 years 11 months ago
Genetic programming with polymorphic types and higher-order functions
This article introduces our new approach to program representation for genetic programming (GP). We replace the usual s-expression representation scheme by a strongly-typed ion-ba...
Franck Binard, Amy P. Felty
GECCO
2006
Springer
124views Optimization» more  GECCO 2006»
14 years 1 months ago
On evolving buffer overflow attacks using genetic programming
In this work, we employed genetic programming to evolve a "white hat" attacker; that is to say, we evolve variants of an attack with the objective of providing better de...
Hilmi Günes Kayacik, Malcolm I. Heywood, A. N...