19 search results - page 2 / 4 » Local Regularized Least-Square Dimensionality Reduction |
130
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TNN
2008
15 years 1 months ago
2008
In this paper, a new kernel-based method for data visualization and dimensionality reduction is proposed. A reference point is considered corresponding to additional constraints ta...
126
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ICML
2007
IEEE
16 years 2 months ago
2007
IEEE
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
116
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KDD
2010
ACM
15 years 3 months ago
2010
ACM
Dimensionality reduction plays an important role in many data mining applications involving high-dimensional data. Many existing dimensionality reduction techniques can be formula...
151
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ICCV
2007
IEEE
16 years 3 months ago
2007
IEEE
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
118
Voted
JMLR
2010
14 years 8 months ago
2010
Fisher linear discriminant analysis (FDA) and its kernel extension--kernel discriminant analysis (KDA)--are well known methods that consider dimensionality reduction and classific...