98 search results - page 9 / 20 » Regression on manifolds using kernel dimension reduction |
ICML
2004
IEEE
14 years 7 months ago
2004
IEEE
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
CVPR
2008
IEEE
13 years 6 months ago
2008
IEEE
Learning a robust projection with a small number of training samples is still a challenging problem in face recognition, especially when the unseen faces have extreme variation in...
CVPR
2010
IEEE
14 years 2 months ago
2010
IEEE
We introduce a parametric version (pDRUR) of the recently proposed Dimensionality Reduction by Unsupervised Regression algorithm. pDRUR alternately minimizes reconstruction error ...
JMLR
2010
13 years 1 months ago
2010
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
CVPR
2010
IEEE
13 years 12 months ago
2010
IEEE
Non-negative matrix factorization (NMF) is an excellent tool for unsupervised parts-based learning, but proves to be ineffective when parts of a whole follow a specific pattern. ...