A convenient way of dealing with image sets is to represent them as points on Grassmannian manifolds. While several recent studies explored the applicability of discriminant analy...
The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications such as face recognition. Re...
Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladi...
In this paper, we discuss fuzzy classifiers based on Kernel Discriminant Analysis (KDA) for two-class problems. In our method, first we employ KDA to the given training data and ca...