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GECCO
2010
Springer
158views Optimization» more  GECCO 2010»
15 years 2 months ago
A genetic algorithm to improve linux kernel performance on resource-constrained devices
As computers become increasingly mobile, users demand more functionality, longer battery-life, and better performance from mobile devices. In response, chipset fabricators are foc...
James Kukunas, Robert D. Cupper, Gregory M. Kapfha...
GECCO
2010
Springer
157views Optimization» more  GECCO 2010»
15 years 1 months ago
Speeding up the evaluation of evolutionary learning systems using GPGPUs
In this paper we introduce a method for computing fitness in evolutionary learning systems based on NVIDIA’s massive parallel technology using the CUDA library. Both the match ...
María A. Franco, Natalio Krasnogor, Jaume B...
GECCO
2010
Springer
141views Optimization» more  GECCO 2010»
15 years 27 days ago
Today/future importance analysis
SBSE techniques have been widely applied to requirements selection and prioritization problems in order to ascertain a suitable set of requirements for the next release of a syste...
Yuanyuan Zhang, Enrique Alba, Juan J. Durillo, Sig...
GECCO
2010
Springer
184views Optimization» more  GECCO 2010»
15 years 2 months ago
Transfer learning through indirect encoding
An important goal for the generative and developmental systems (GDS) community is to show that GDS approaches can compete with more mainstream approaches in machine learning (ML)....
Phillip Verbancsics, Kenneth O. Stanley
GECCO
2010
Springer
155views Optimization» more  GECCO 2010»
15 years 2 months ago
Negative selection algorithms without generating detectors
Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of ...
Maciej Liskiewicz, Johannes Textor