NIPS
2004
14 years 25 days 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 26 days 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 6 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 1 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...