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» Unsupervised Nonlinear Manifold Learning
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NIPS
2001
13 years 9 months ago
Global Coordination of Local Linear Models
High dimensional data that lies on or near a low dimensional manifold can be described by a collection of local linear models. Such a description, however, does not provide a glob...
Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinto...
PR
2007
127views more  PR 2007»
13 years 7 months ago
Face recognition using spectral features
Face recognition is a challenging task in computer vision and pattern recognition. It is well-known that obtaining a low-dimensional feature representation with enhanced discrimin...
Fei Wang, Jingdong Wang, Changshui Zhang, James T....
AAAI
2007
13 years 10 months ago
Isometric Projection
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
Deng Cai, Xiaofei He, Jiawei Han
TIP
2002
179views more  TIP 2002»
13 years 7 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
ICML
2010
IEEE
13 years 8 months ago
Improved Local Coordinate Coding using Local Tangents
Local Coordinate Coding (LCC), introduced in (Yu et al., 2009), is a high dimensional nonlinear learning method that explicitly takes advantage of the geometric structure of the d...
Kai Yu, Tong Zhang