178 search results - page 1 / 36 » Extensions of Manifold Learning Algorithms in Kernel Feature... |
ISNN
2007
Springer
13 years 10 months ago
2007
Springer
Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a ...
ICML
2004
IEEE
13 years 9 months ago
2004
IEEE
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
PR
2010
13 years 2 months ago
2010
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
ICCV
2005
IEEE
13 years 10 months ago
2005
IEEE
This paper investigates the appearance manifold of facial expression: embedding image sequences of facial expression from the high dimensional appearance feature space to a low dim...
CVPR
2007
IEEE
14 years 6 months ago
2007
IEEE
Kernel methods have been widely studied in the field of pattern recognition. These methods implicitly map, "the kernel trick," the data into a space which is more approp...