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» Modeling GA Performance for Control Parameter Optimization
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98
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NIPS
1998
15 years 3 months ago
Dynamically Adapting Kernels in Support Vector Machines
The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
Nello Cristianini, Colin Campbell, John Shawe-Tayl...
120
Voted
BMVC
2010
14 years 12 months ago
Improved Anatomical Landmark Localization in Medical Images Using Dense Matching of Graphical Models
We propose a method for reliably and accurately identifying anatomical landmarks in 3D CT volumes based on dense matching of parts-based graphical models. Such a system can be use...
Vaclav Potesil, Timor Kadir, Günther Platsch,...
117
Voted
WINET
2002
124views more  WINET 2002»
15 years 1 months ago
Improving Energy Efficiency of Centrally Controlled Wireless Data Networks
Wireless network access protocols can assist nodes to conserve energy by identifying when they can enter low energy states. The goal is to put all nodes not involved in a transmiss...
John A. Stine, Gustavo de Veciana
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
15 years 2 months ago
Application domain study of evolutionary algorithms in optimization problems
This paper deals with the problem of comparing and testing evolutionary algorithms, that is, the benchmarking problem, from an analysis point of view. A practical study of the app...
Pilar Caamaño, Francisco Bellas, José...
126
Voted
APIN
2000
120views more  APIN 2000»
15 years 1 months ago
Two-Loop Real-Coded Genetic Algorithms with Adaptive Control of Mutation Step Sizes
Genetic algorithms are adaptive methods based on natural evolution that may be used for search and optimization problems. They process a population of search space solutions with t...
Francisco Herrera, Manuel Lozano