Sciweavers

GECCO
2007
Springer
150views Optimization» more  GECCO 2007»
13 years 8 months ago
Overcoming hierarchical difficulty by hill-climbing the building block structure
The Building Block Hypothesis suggests that Genetic Algorithms (GAs) are well-suited for hierarchical problems, where efficient solving requires proper problem decomposition and a...
David Iclanzan, Dan Dumitrescu
GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
13 years 8 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
2007
Springer
159views Optimization» more  GECCO 2007»
13 years 8 months ago
Discrimination of metabolic flux profiles using a hybrid evolutionary algorithm
Studying metabolic fluxes is a crucial aspect of understanding biological phenotypes. However, it is often not possible to measure these fluxes directly. As an alternative, fluxom...
Stefan Bleuler, Eckart Zitzler
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
13 years 8 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa
GECCO
2007
Springer
215views Optimization» more  GECCO 2007»
13 years 8 months ago
Finding safety errors with ACO
Model Checking is a well-known and fully automatic technique for checking software properties, usually given as temporal logic formulae on the program variables. Most model checke...
Enrique Alba, J. Francisco Chicano
GECCO
2007
Springer
142views Optimization» more  GECCO 2007»
13 years 8 months ago
Graph structured program evolution
Shinichi Shirakawa, Shintaro Ogino, Tomoharu Nagao
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
13 years 8 months ago
A new crossover technique for Cartesian genetic programming
Genetic Programming was first introduced by Koza using tree representation together with a crossover technique in which random sub-branches of the parents' trees are swapped ...
Janet Clegg, James Alfred Walker, Julian Francis M...
GECCO
2007
Springer
144views Optimization» more  GECCO 2007»
13 years 8 months ago
The reliability of confidence intervals for computational effort comparisons
This paper analyses the reliability of confidence intervals for Koza's computational effort statistic. First, we conclude that dependence between the observed minimum generat...
Matthew Walker, Howard Edwards, Chris H. Messom
GECCO
2007
Springer
159views Optimization» more  GECCO 2007»
13 years 8 months ago
Uniform sampling of local pareto-optimal solution curves by pareto path following and its applications in multi-objective GA
Although multi-objective GA (MOGA) is an efficient multiobjective optimization (MOO) method, it has some limitations that need to be tackled, which include unguaranteed uniformity...
Ken Harada, Jun Sakuma, Shigenobu Kobayashi, Isao ...
GECCO
2007
Springer
206views Optimization» more  GECCO 2007»
13 years 8 months ago
Using code metric histograms and genetic algorithms to perform author identification for software forensics
We have developed a technique to characterize software developers' styles using a set of source code metrics. This style fingerprint can be used to identify the likely author...
Robert Charles Lange, Spiros Mancoridis