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» Feature Subset Selection Using a Genetic Algorithm
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166
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GECCO
2009
Springer
258views Optimization» more  GECCO 2009»
15 years 7 months ago
Evolutionary learning of local descriptor operators for object recognition
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Cynthia B. Pérez, Gustavo Olague
123
Voted
COMPSAC
2007
IEEE
15 years 6 months ago
AOP-based automated unit test classification of large benchmarks
Despite the availability of a variety of program analysis tools, evaluation of these tools is difficult, as only few benchmark suites exist. Existing benchmark suites lack the uni...
Cyrille Artho, Zhongwei Chen, Shinichi Honiden
122
Voted
KDD
2008
ACM
213views Data Mining» more  KDD 2008»
16 years 3 months ago
Heterogeneous data fusion for alzheimer's disease study
Effective diagnosis of Alzheimer's disease (AD) is of primary importance in biomedical research. Recent studies have demonstrated that neuroimaging parameters are sensitive a...
Jieping Ye, Kewei Chen, Teresa Wu, Jing Li, Zheng ...
125
Voted
SIGIR
2002
ACM
15 years 2 months ago
Document clustering with cluster refinement and model selection capabilities
In this paper, we propose a document clustering method that strives to achieve: (1) a high accuracy of document clustering, and (2) the capability of estimating the number of clus...
Xin Liu, Yihong Gong, Wei Xu, Shenghuo Zhu
128
Voted
CEC
2008
IEEE
15 years 9 months ago
A multi-agent based evolutionary algorithm in non-stationary environments
— In this paper, a multi-agent based evolutionary algorithm (MAEA) is introduced to solve dynamic optimization problems. The agents simulate living organism features and co-evolv...
Yang Yan, Hongfeng Wang, Dingwei Wang, Shengxiang ...