194 search results - page 8 / 39 » Subspace Regularization: A New Semi-supervised Learning Meth... |
107
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ECML
2007
Springer
15 years 5 months ago
2007
Springer
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
84
Voted
ALT
2006
Springer
15 years 8 months ago
2006
Springer
Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
96
Voted
ICDM
2007
IEEE
15 years 3 months ago
2007
IEEE
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
121
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ECML
2007
Springer
15 years 5 months ago
2007
Springer
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
113
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CVPR
2007
IEEE
16 years 1 months ago
2007
IEEE
Subspace learning based face recognition methods have attracted considerable interests in recently years, including Principal Component Analysis (PCA), Linear Discriminant Analysi...