This paper introduces a novel nonlinear extension of Fisher's classical linear discriminant analysis (FDA) known as high-order Fisher's discriminant analysis (HOFDA). Th...
A Generalized Nonlinear Discriminant Analysis (GNDA) method is proposed, which implements Fisher discriminant analysis in a nonlinear mapping space. Linear discriminant analysis i...
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 propose to investigate test statistics for testing homogeneity based on kernel Fisher discriminant analysis. Asymptotic null distributions under null hypothesis are derived, an...
—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...