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GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
14 years 1 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
GECCO
2005
Springer
122views Optimization» more  GECCO 2005»
14 years 3 months ago
An enhanced GA to improve the search process reliability in tuning of control systems
Evolutionary Algorithms (EAs) have been largely applied to optimisation and synthesis of controllers. In spite of several successful applications and competitive solutions, the st...
Andrea Soltoggio
GECCO
2004
Springer
132views Optimization» more  GECCO 2004»
14 years 3 months ago
Robust and Efficient Genetic Algorithms with Hierarchical Niching and a Sustainable Evolutionary Computation Model
This paper proposes a new niching method named hierarchical niching, which combines spatial niching in search space and a continuous temporal niching concept. The method is natural...
Jianjun Hu, Erik D. Goodman
GECCO
2007
Springer
258views Optimization» more  GECCO 2007»
14 years 2 months ago
TFBS identification by position- and consensus-led genetic algorithm with local filtering
Identification of Transcription Factor Binding Site (TFBS) motifs in multiple DNA upstream sequences is important in understanding the mechanism of gene regulation. This identific...
Tak-Ming Chan, Kwong-Sak Leung, Kin-Hong Lee
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
14 years 4 months ago
Towards billion-bit optimization via a parallel estimation of distribution algorithm
This paper presents a highly efficient, fully parallelized implementation of the compact genetic algorithm (cGA) to solve very large scale problems with millions to billions of va...
Kumara Sastry, David E. Goldberg, Xavier Llor&agra...