31 search results - page 3 / 7 » Learning Linear Discriminant Projections for Dimensionality ... |
ICIP
2005
IEEE
14 years 7 months ago
2005
IEEE
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
CVPR
2008
IEEE
13 years 5 months ago
2008
IEEE
Learning a robust projection with a small number of training samples is still a challenging problem in face recognition, especially when the unseen faces have extreme variation in...
ECCV
2010
Springer
13 years 10 months 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...
ICDM
2007
IEEE
13 years 9 months ago
2007
IEEE
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
AAAI
2008
13 years 7 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 ...