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» Genetic Search Based on Multiple Mutations
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FOGA
1998
14 years 10 months ago
Understanding Interactions among Genetic Algorithm Parameters
Genetic algorithms (GAs) are multi-dimensional and stochastic search methods, involving complex interactions among their parameters. For last two decades, researchers have been tr...
Kalyanmoy Deb, Samir Agrawal
72
Voted
BMCBI
2010
208views more  BMCBI 2010»
14 years 9 months ago
A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y....
CIVR
2005
Springer
123views Image Analysis» more  CIVR 2005»
15 years 3 months ago
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Chengcui Zhang, Xin Chen
GECCO
2005
Springer
140views Optimization» more  GECCO 2005»
15 years 2 months ago
MDGA: motif discovery using a genetic algorithm
Computationally identifying transcription factor binding sites in the promoter regions of genes is an important problem in computational biology and has been under intensive resea...
Dongsheng Che, Yinglei Song, Khaled Rasheed
GECCO
2003
Springer
155views Optimization» more  GECCO 2003»
15 years 2 months ago
Adaptive Elitist-Population Based Genetic Algorithm for Multimodal Function Optimization
Abstract. This paper introduces a new technique called adaptive elitistpopulation search method for allowing unimodal function optimization methods to be extended to efficiently lo...
Kwong-Sak Leung, Yong Liang