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EMO
2006
Springer
107views Optimization» more  EMO 2006»
15 years 10 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 6 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
GECCO
2007
Springer
164views Optimization» more  GECCO 2007»
16 years 20 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