54 search results - page 3 / 11 » Exploiting Feature Covariance in High-Dimensional Online Lea... |
CVPR
2008
IEEE
14 years 8 months ago
2008
IEEE
Recently, a novel Log-Euclidean Riemannian metric [28] is proposed for statistics on symmetric positive definite (SPD) matrices. Under this metric, distances and Riemannian means ...
CVPR
2003
IEEE
14 years 8 months ago
2003
IEEE
We introduce the problem of repetitive nearest neighbor search in relevance feedback and propose an efficient search scheme for high dimensional feature spaces. Relevance feedback...
ACL
1998
13 years 7 months ago
1998
We present an architecture and an on-line learning algorithm and apply it to the problem of part-ofspeech tagging. The architecture presented, SNOW, is a network of linear separat...
MICCAI
2005
Springer
14 years 7 months ago
2005
Springer
Functional Magnetic Resonance Imaging(fMRI) has enabled scientists to look into the active human brain, leading to a flood of new data, thus encouraging the development of new data...
ICCV
2011
IEEE
12 years 6 months ago
2011
IEEE
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...