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» Function Optimization with Coevolutionary Algorithms
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GECCO
2005
Springer
128views Optimization» more  GECCO 2005»
14 years 3 months ago
Fitness-based neighbor selection for multimodal function optimization
We propose a selection scheme called Fitness-based Neighbor Selection (FNS) for multimodal optimization. The FNS is aimed for ill-scaled and locally multimodal domain, both found ...
Shin Ando, Shigenobu Kobayashi
CEC
2007
IEEE
14 years 4 months ago
Differential evolution for high-dimensional function optimization
— Most reported studies on differential evolution (DE) are obtained using low-dimensional problems, e.g., smaller than 100, which are relatively small for many real-world problem...
Zhenyu Yang, Ke Tang, Xin Yao
CEC
2010
IEEE
13 years 11 months ago
Learning-assisted evolutionary search for scalable function optimization: LEM(ID3)
Inspired originally by the Learnable Evolution Model(LEM) [5], we investigate LEM(ID3), a hybrid of evolutionary search with ID3 decision tree learning. LEM(ID3) involves interleav...
Guleng Sheri, David Corne
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 11 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
JC
2007
101views more  JC 2007»
13 years 9 months ago
Simple Monte Carlo and the Metropolis algorithm
We study the integration of functions with respect to an unknown density. Information is available as oracle calls to the integrand and to the nonnormalized density function. We ar...
Peter Mathé, Erich Novak