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» Stable feature selection via dense feature groups
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113
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KDD
2008
ACM
264views Data Mining» more  KDD 2008»
15 years 10 months ago
Stable feature selection via dense feature groups
Many feature selection algorithms have been proposed in the past focusing on improving classification accuracy. In this work, we point out the importance of stable feature selecti...
Lei Yu, Chris H. Q. Ding, Steven Loscalzo
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
15 years 10 months ago
Consensus group stable feature selection
Stability is an important yet under-addressed issue in feature selection from high-dimensional and small sample data. In this paper, we show that stability of feature selection ha...
Steven Loscalzo, Lei Yu, Chris H. Q. Ding
99
Voted
UAI
2008
14 years 11 months ago
Feature Selection via Block-Regularized Regression
Identifying co-varying causal elements in very high dimensional feature space with internal structures, e.g., a space with as many as millions of linearly ordered features, as one...
Seyoung Kim, Eric P. Xing
KDD
2010
ACM
326views Data Mining» more  KDD 2010»
14 years 7 months ago
Document clustering via dirichlet process mixture model with feature selection
One essential issue of document clustering is to estimate the appropriate number of clusters for a document collection to which documents should be partitioned. In this paper, we ...
Guan Yu, Ruizhang Huang, Zhaojun Wang
83
Voted
CVPR
2010
IEEE
15 years 5 months ago
Automatic Image Annotation Using Group Sparsity
Automatically assigning relevant text keywords to images is an important problem. Many algorithms have been proposed in the past decade and achieved good performance. Efforts have...
Shaoting Zhang, Junzhou Huang, Yuchi Huang, Yang Y...