73 search results - page 1 / 15 » Sparse Unsupervised Dimensionality Reduction Algorithms |
PKDD
2010
Springer
13 years 4 months ago
2010
Springer
Abstract. Principal component analysis (PCA) and its dual—principal coordinate analysis (PCO)—are widely applied to unsupervised dimensionality reduction. In this paper, we sho...
ICPR
2010
IEEE
13 years 11 months ago
2010
IEEE
Face recognition (FR) is an active yet challenging topic in computer vision applications. As a powerful tool to represent high dimensional data, recently sparse representation bas...
ICML
2005
IEEE
14 years 7 months ago
2005
IEEE
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
IJPRAI
2010
13 years 3 months ago
2010
: Many locality-based unsupervised dimensionality reduction (DR) algorithms have recently been proposed and demonstrated to be effective to a certain degree in some classification ...
CVPR
2006
IEEE
14 years 8 months ago
2006
IEEE
In this paper, we present a novel approach to learning semantic localized patterns with binary projections in a supervised manner. The pursuit of these binary projections is refor...