Kernel Fisher discriminant analysis (KFDA) is a popular classification technique which requires the user to predefine an appropriate kernel. Since the performance of KFDA depends on the choice of the kernel, the problem of kernel selection becomes very important. In this paper we treat the...

We propose a proximal version of the knowledge based support vector machine formulation, termed as knowledge based proximal support vector machines (KBPSVMs) in the sequel, for binary data classification. The KBPSVM classifier incorporates prior knowledge in the form of multiple polyhedral sets,...

A fractional analogue of Sinha's problem [Sinha, S. M. 1966. A duality theorem for nonlinear programming. Management Sci. 12 385.] is considered and duality theory is developed for it. This duality subsumes duality results of Chadha [Chadha, S. S. 1971. A dual fractional program. ZAMM 51 560.]...

In this article, we study nonsmooth convex minimax programming problems with cone constraint and abstract constraint. Our aim is to develop sequential Lagrange multiplier rules for this class of problems in the absence of any constraint qualification. These rules are obtained in terms of...