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» Computational complexity and evolutionary computation
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142
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GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
15 years 7 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa
157
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ML
2000
ACM
244views Machine Learning» more  ML 2000»
15 years 3 months ago
Learnable Evolution Model: Evolutionary Processes Guided by Machine Learning
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombinat...
Ryszard S. Michalski
135
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CEC
2007
IEEE
15 years 5 months ago
A novel general framework for evolutionary optimization: Adaptive fuzzy fitness granulation
— Computational complexity is a major challenge in evolutionary algorithms due to their need for repeated fitness function evaluations. Here, we aim to reduce number of fitness f...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...
96
Voted
CEC
2005
IEEE
15 years 9 months ago
Multiobjective financial portfolio design: a hybrid evolutionary approach
—A principal challenge in modern computational finance is efficient portfolio design – portfolio optimization followed by decision-making. Optimization based on even the widely...
Raj Subbu, Piero P. Bonissone, Neil Eklund, Sriniv...
126
Voted
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
15 years 4 months ago
An evolutionary approach for competency-based curriculum sequencing
The process of creating e-learning contents using reusable learning objects (LOs) can be broken down in two sub-processes: LOs finding and LO sequencing. Sequencing is usually per...
Luis de Marcos, José-Javier Martínez...