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119
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GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
15 years 6 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
TEC
2008
150views more  TEC 2008»
15 years 2 months ago
AbYSS: Adapting Scatter Search to Multiobjective Optimization
We propose the use of a new algorithm to solve multiobjective optimization problems. Our proposal adapts the well-known scatter search template for single objective optimization to...
Antonio J. Nebro, Francisco Luna, Enrique Alba, Be...
117
Voted
CEC
2010
IEEE
15 years 19 days ago
Comparison of GA and PSO performance in parameter estimation of microbial growth models: A case-study using experimental data
In this work we examined the performance of two evolutionary algorithms, a genetic algorithm (GA) and particle swarm optimization (PSO), in the estimation of the parameters of a mo...
Dulce Calcada, Agostinho Rosa, Luis C. Duarte, Vit...
126
Voted
GECCO
2007
Springer
213views Optimization» more  GECCO 2007»
15 years 6 months ago
Aspects of adaptation in natural and artificial evolution
This work addresses selected aspects of natural evolution, especially of the field of population genetics, that are considered to be meaningful for algorithmic further development...
Michael Affenzeller, Stefan Wagner 0002, Stephan M...
GPEM
2002
163views more  GPEM 2002»
15 years 2 months ago
Fast Ant Colony Optimization on Runtime Reconfigurable Processor Arrays
Ant Colony Optimization (ACO) is a metaheuristic used to solve combinatorial optimization problems. As with other metaheuristics, like evolutionary methods, ACO algorithms often sh...
Daniel Merkle, Martin Middendorf