35 search results - page 5 / 7 » Symmetric two dimensional linear discriminant analysis (2DLD... |
CVPR
2005
IEEE
14 years 9 months ago
2005
IEEE
In the last decades, a large family of algorithms supervised or unsupervised; stemming from statistic or geometry theory have been proposed to provide different solutions to the p...
AAAI
2008
13 years 9 months ago
2008
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
ACII
2005
Springer
13 years 9 months ago
2005
Springer
The null space N(St) of total scatter matrix St contains no useful information for pattern classification. So, discarding the null space N(St) results in dimensionality reduction ...
ECCV
2010
Springer
14 years 15 days ago
2010
Springer
This paper presents algorithms for efficiently computing the covariance matrix for features that form sub-windows in a large multidimensional image. For example, several image proc...