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GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
13 years 12 months ago
Expensive optimization, uncertain environment: an EA-based solution
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Maumita Bhattacharya
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
13 years 6 months ago
Potential fitness for genetic programming
We introduce potential fitness, a variant of fitness function that operates in the space of schemata and is applicable to tree-based genetic programing. The proposed evaluation ...
Krzysztof Krawiec, PrzemysBaw Polewski
GECCO
2006
Springer
207views Optimization» more  GECCO 2006»
13 years 9 months ago
Both robust computation and mutation operation in dynamic evolutionary algorithm are based on orthogonal design
A robust dynamic evolutionary algorithm (labeled RODEA), where both the robust calculation and mutation operator are based on an orthogonal design, is proposed in this paper. Prev...
Sanyou Y. Zeng, Rui Wang, Hui Shi, Guang Chen, Hug...
ANTSW
2008
Springer
13 years 7 months ago
Adaptive Particle Swarm Optimization
An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perfor...
Zhi-hui Zhan, Jun Zhang
CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 5 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...