NIPS
2004
14 years 1 months ago
2004
We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...
SDM
2007
SIAM
14 years 1 months ago
2007
SIAM
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
ICASSP
2009
IEEE
14 years 7 months ago
2009
IEEE
Diffusion Maps (DiffMaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including Laplacian Eigenmaps, and it has become ...
ICIP
2006
IEEE
15 years 2 months ago
2006
IEEE
An important class of image data sets depict an object undergoing deformation. When there are only a few underlying causes of the deformation, these images have a natural lowdimen...