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» Competitive Self-adaptation in Evolutionary Algorithms
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CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 7 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
BMCBI
2010
113views more  BMCBI 2010»
13 years 7 months ago
Efficient protein alignment algorithm for protein search
Background: Proteins show a great variety of 3D conformations, which can be used to infer their evolutionary relationship and to classify them into more general groups; therefore ...
Zaixin Lu, Zhiyu Zhao, Bin Fu
ISICA
2007
Springer
14 years 1 months ago
Fast Multi-swarm Optimization with Cauchy Mutation and Crossover Operation
The standard Particle Swarm Optimization (PSO) algorithm is a novel evolutionary algorithm in which each particle studies its own previous best solution and the group’s previous ...
Qing Zhang, Changhe Li, Yong Liu, Lishan Kang
TEC
2008
150views more  TEC 2008»
13 years 7 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...
CEC
2009
IEEE
14 years 2 months ago
Hyper-learning for population-based incremental learning in dynamic environments
— The population-based incremental learning (PBIL) algorithm is a combination of evolutionary optimization and competitive learning. Recently, the PBIL algorithm has been applied...
Shengxiang Yang, Hendrik Richter