93 search results - page 10 / 19 » Greedy Kernel Principal Component Analysis |
PAMI
2002
13 years 9 months ago
2002
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
ICIC
2009
Springer
14 years 4 months ago
2009
Springer
Now the classification of different tumor types is of great importance in cancer diagnosis and drug discovery. It is more desirable to create an optimal ensemble for data analysis ...
ICCV
2009
IEEE
13 years 7 months ago
2009
IEEE
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
PAMI
2010
13 years 8 months ago
2010
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
CVPR
2006
IEEE
14 years 12 months ago
2006
IEEE
A fast algorithm, Accelerated Kernel Feature Analysis (AKFA), that discovers salient features evidenced in a sample of n unclassified patterns, is presented. Like earlier kernel-b...