540 search results - page 7 / 108 » Dimensionality Reduction for Data in Multiple Feature Repres... |
SDM
2007
SIAM
13 years 8 months 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...
SDM
2010
SIAM
13 years 8 months ago
2010
SIAM
The dimensionality reduction problem has been widely studied in the database literature because of its application for concise data representation in a variety of database applica...
ACL
2010
13 years 4 months ago
2010
We initiate a study comparing effectiveness of the transformed spaces learned by recently proposed supervised, and semisupervised metric learning algorithms to those generated by ...
ICCV
2011
IEEE
12 years 6 months ago
2011
IEEE
Low-Rank Representation (LRR) [16, 17] is an effective method for exploring the multiple subspace structures of data. Usually, the observed data matrix itself is chosen as the dic...
TNN
2008
13 years 6 months ago
2008
In this paper, a new kernel-based method for data visualization and dimensionality reduction is proposed. A reference point is considered corresponding to additional constraints ta...