The theoretical analysis of kernel technique and its applications
Qing Tao, Jiaqi Wang, Gaowei Wu, Jue Wang · 2003
Investigates linear separability in feature space from Tietze extension theorem and function approximation theory, and kernel technique is motivated theoretically. Two kernel-based algorithms are presented. One of them is a general learning algorithm for feedforward neural networks, and they can solve large-scale classification problems.