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AAAI
2010
13 years 11 months ago
Efficient Spectral Feature Selection with Minimum Redundancy
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...
Zheng Zhao, Lei Wang, Huan Liu
SPLC
2007
13 years 11 months ago
Automating Product-Line Variant Selection for Mobile Devices
Abstract—Product-line architectures (PLAs) designed for mobile devices create a unique challenge for automated product variant selection engines since variants must be derived on...
Jules White, Douglas C. Schmidt, Egon Wuchner, And...
TNN
2010
154views Management» more  TNN 2010»
13 years 4 months ago
Discriminative semi-supervised feature selection via manifold regularization
We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number ...
Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin
ICML
2006
IEEE
14 years 11 months ago
Feature subset selection bias for classification learning
Feature selection is often applied to highdimensional data prior to classification learning. Using the same training dataset in both selection and learning can result in socalled ...
Surendra K. Singhi, Huan Liu
PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
14 years 4 months ago
Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC)
Abstract. We address the problem of joint feature selection in multiple related classification or regression tasks. When doing feature selection with multiple tasks, usually one c...
Paramveer S. Dhillon, Brian Tomasik, Dean P. Foste...