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GECCO
2008
Springer
123views Optimization» more  GECCO 2008»
13 years 10 months ago
Hierarchical evolution of linear regressors
We propose an algorithm for function approximation that evolves a set of hierarchical piece-wise linear regressors. The algorithm, named HIRE-Lin, follows the iterative rule learn...
Francesc Teixidó-Navarro, Albert Orriols-Pu...
BMCBI
2008
142views more  BMCBI 2008»
13 years 9 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
EUSFLAT
2003
174views Fuzzy Logic» more  EUSFLAT 2003»
13 years 10 months ago
Evolvable fuzzy controllers using parallel evolutionary algorithms
We are trying to piece together the knowledge of evolution with the help of biology, informatics and physics to create complex evolutionary algorithms with parallel and hierarchic...
Pavel Osmera
ICTAI
2009
IEEE
14 years 3 months ago
A Multi-objective Genetic Algorithm for Community Detection in Networks
A multiobjective genetic algorithm to uncover community structure in complex network is proposed. The algorithm optimizes two objective functions able to identify densely connecte...
Clara Pizzuti
EMO
2003
Springer
81views Optimization» more  EMO 2003»
14 years 2 months ago
Solving Hierarchical Optimization Problems Using MOEAs
Abstract. In this paper, we propose an approach for solving hierarchical multi-objective optimization problems (MOPs). In realistic MOPs, two main challenges have to be considered:...
Christian Haubelt, Sanaz Mostaghim, Jürgen Te...