137 search results - page 23 / 28 » Ordinal Embedding: Approximation Algorithms and Dimensionali... |
CGF
1998
13 years 7 months ago
1998
A multiresolution data decomposition offers a fundamental framework supporting compression, progressive transmission, and level-of-detail (LOD) control for large two or three dime...
IVC
2007
13 years 7 months ago
2007
- Canonical correlation analysis (CCA) is a major linear subspace approach to dimensionality reduction and has been applied to image processing, pose estimation and other fields. H...
MM
2010
ACM
13 years 8 months ago
2010
ACM
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
CVPR
2001
IEEE
14 years 9 months ago
2001
IEEE
Isometric surfaces share the same geometric structure also known as the `first fundamental form'. For example, all possible bending of a given surface, that include all lengt...