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» Computational complexity and evolutionary computation
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95
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GECCO
2005
Springer
116views Optimization» more  GECCO 2005»
15 years 9 months ago
Measuring, enabling and comparing modularity, regularity and hierarchy in evolutionary design
For computer-automated design systems to scale to complex designs they must be able to produce designs that exhibit the characteristics of modularity, regularity and hierarchy –...
Gregory Hornby
151
Voted
GECCO
2003
Springer
127views Optimization» more  GECCO 2003»
15 years 9 months ago
Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data
Abstract. Our ability to simultaneously measure the expression levels of thousands of genes in biological samples is providing important new opportunities for improving the diagnos...
David M. Reif, Bill C. White, Nancy Olsen, Thomas ...
126
Voted
GECCO
2005
Springer
130views Optimization» more  GECCO 2005»
15 years 9 months ago
Quality-time analysis of multi-objective evolutionary algorithms
A quality-time analysis of multi-objective evolutionary algorithms (MOEAs) based on schema theorem and building blocks hypothesis is developed. A bicriteria OneMax problem, a hypo...
Jian-Hung Chen, Shinn-Ying Ho, David E. Goldberg
156
Voted
PPSN
2004
Springer
15 years 9 months ago
Coupling of Evolution and Learning to Optimize a Hierarchical Object Recognition Model
Abstract. A key problem in designing artificial neural networks for visual object recognition tasks is the proper choice of the network architecture. Evolutionary optimization met...
Georg Schneider, Heiko Wersing, Bernhard Sendhoff,...
137
Voted
BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
15 years 10 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...