399 search results - page 21 / 80 » Two-Dimensional Linear Discriminant Analysis |
CVPR
2007
IEEE
14 years 10 months ago
2007
IEEE
Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
SIBGRAPI
2009
IEEE
14 years 3 months ago
2009
IEEE
We have designed and implemented a multi-linear discriminant method of constructing and quantifying statistically significant changes on human identity photographs. The method is...
SIAMMAX
2010
13 years 3 months ago
2010
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
ESANN
2007
13 years 10 months ago
2007
Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernel...
ICDM
2009
IEEE
14 years 3 months ago
2009
IEEE
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...