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» A kernel view of the dimensionality reduction of manifolds
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ICML
2004
IEEE
14 years 6 months ago
A kernel view of the dimensionality reduction of manifolds
Bernhard Schölkopf, Daniel D. Lee, Jihun Ham,...
ICML
2004
IEEE
13 years 10 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
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 ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
ICCV
2009
IEEE
14 years 10 months ago
Dimensionality Reduction and Principal Surfaces via Kernel Map Manifolds
We present a manifold learning approach to dimensionality reduction that explicitly models the manifold as a mapping from low to high dimensional space. The manifold is represen...
Samuel Gerber, Tolga Tasdizen, Ross Whitaker
ICML
2007
IEEE
14 years 6 months ago
Regression on manifolds using kernel dimension reduction
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...
Jens Nilsson, Fei Sha, Michael I. Jordan
ICPR
2006
IEEE
14 years 6 months ago
Simultaneous Inference of View and Body Pose using Torus Manifolds
Inferring 3D body pose as well as viewpoint from a single silhouette image is a challenging problem. We present a new generative model to represent shape deformations according to...
Ahmed M. Elgammal, Chan-Su Lee