It is generally believed that quadratic discriminant analysis (QDA) can better fit the data in practical pattern recognition applications compared to linear discriminant analysis ...
Jie Wang, Konstantinos N. Plataniotis, Juwei Lu, A...
We describe a fast algorithm for kernel discriminant analysis, empirically demonstrating asymptotic speed-up over the previous best approach. We achieve this with a new pattern of...
In order to overcome the computation and storage problem for large-scale data set, an efficient iterative method of Generalized Discriminant Analysis is proposed. Because sample v...
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
It was prescriptive that an image matrix was transformed into a vector before the kernel-based subspace learning. In this paper, we take the Kernel Discriminant Analysis (KDA) alg...
Shuicheng Yan, Dong Xu, Lei Zhang, Benyu Zhang, Ho...