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» Robust Feature Selection Algorithms
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CEC
2005
IEEE
14 years 2 months ago
Parallel evolutionary algorithms on graphics processing unit
Evolutionary Algorithms (EAs) are effective and robust methods for solving many practical problems such as feature selection, electrical circuits synthesis, and data mining. Howeve...
Man Leung Wong, Tien-Tsin Wong, Ka-Ling Fok
ACCV
2006
Springer
14 years 3 months ago
Attractor-Guided Particle Filtering for Lip Contour Tracking
Abstract. We present a lip contour tracking algorithm using attractorguided particle filtering. Usually it is difficult to robustly track the lip contour because the lip contour i...
Yong-Dian Jian, Wen-Yan Chang, Chu-Song Chen
CORR
2011
Springer
200views Education» more  CORR 2011»
13 years 4 months ago
Using Feature Weights to Improve Performance of Neural Networks
Different features have different relevance to a particular learning problem. Some features are less relevant; while some very important. Instead of selecting the most relevant fe...
Ridwan Al Iqbal
JMLR
2006
85views more  JMLR 2006»
13 years 9 months ago
Streamwise Feature Selection
In streamwise feature selection, new features are sequentially considered for addition to a predictive model. When the space of potential features is large, streamwise feature sel...
Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H...
ICDM
2008
IEEE
107views Data Mining» more  ICDM 2008»
14 years 3 months ago
Graph-Based Iterative Hybrid Feature Selection
When the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. To ...
ErHeng Zhong, Sihong Xie, Wei Fan, Jiangtao Ren, J...