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EMO
2006
Springer
107views Optimization» more  EMO 2006»
15 years 9 months ago
Designing Multi-objective Variation Operators Using a Predator-Prey Approach
In this paper, we propose a new conceptual method for the design, investigation, and evaluation of multi-objective variation operators for evolutionary multi-objective algorithms. ...
Christian Grimme, Joachim Lepping
EOR
2010
116views more  EOR 2010»
15 years 6 months ago
Speeding up continuous GRASP
Continuous GRASP (C-GRASP) is a stochastic local search metaheuristic for finding cost-efficient solutions to continuous global optimization problems subject to box constraints (Hi...
Michael J. Hirsch, Panos M. Pardalos, Mauricio G. ...
IJON
2002
85views more  IJON 2002»
15 years 5 months ago
Learning statistically efficient features for speaker recognition
We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for a speaker. The basis functions learned by the algori...
Gil-Jin Jang, Te-Won Lee, Yung-Hwan Oh
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GECCO
2007
Springer
164views Optimization» more  GECCO 2007»
16 years 9 days ago
Learning building block structure from crossover failure
In the classical binary genetic algorithm, although crossover within a building block (BB) does not always cause a decrease in fitness, any decrease in fitness results from the ...
Zhenhua Li, Erik D. Goodman
PAMI
2011
15 years 1 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang