19 search results - page 2 / 4 » Local Regularized Least-Square Dimensionality Reduction |
TNN
2008
13 years 5 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...
ICML
2007
IEEE
14 years 6 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 ...
KDD
2010
ACM
13 years 7 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...
ICCV
2007
IEEE
14 years 7 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...
JMLR
2010
13 years 11 days 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...