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NIPS
2004
9 years 1 months ago
Non-Local Manifold Tangent Learning
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...
Yoshua Bengio, Martin Monperrus
SDM
2007
SIAM
182views Data Mining» more  SDM 2007»
9 years 1 months ago
Distance Preserving Dimension Reduction for Manifold Learning
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...
Hyunsoo Kim, Haesun Park, Hongyuan Zha
ICASSP
2009
IEEE
9 years 6 months ago
Connecting spectral and spring methods for manifold learning
Diffusion Maps (DiffMaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including Laplacian Eigenmaps, and it has become ...
Shannon M. Hughes, Peter J. Ramadge
ICIP
2006
IEEE
10 years 1 months ago
Image Manifold Interpolation using Free-Form Deformations
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...
Richard Souvenir, Qilong Zhang, Robert Pless
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