We consider the problem of optimally separating two multivariate populations. Robust linear discriminant rules can be obtained by replacing the empirical means and covariance in th...
Linear Discriminant Analysis (LDA) has been a popular method for extracting features that preserves class separability. The projection functions of LDA are commonly obtained by max...
Traditional analysis methods for single-trial classification of electroencephalography (EEG) focus on two types of paradigms: phase locked methods, in which the amplitude of the ...
Christoforos Christoforou, Paul Sajda, Lucas C. Pa...
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
Categorizing multiple objects in images is essentially a structured prediction problem: the label of an object is in general dependent on the labels of other objects in the image....
Qinfeng Shi, Luping Zhou, Li Cheng, Dale Schuurman...