Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
—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...
Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...
In video surveillance, the sizes of face images are very small. However, few works have been done to investigate scalerobust face recognition. Our experiments on appearancebased m...
In classification, with an increasing number of variables, the required number of observations grows drastically. In this paper we present an approach to put into effect the maxi...
- Contiguity Analysis is a straightforward generalization of Linear Discriminant Analysis in which the partition of elements is replaced by a more general graph structure. Applied ...