Wolfe and Mond-Weir type symmetric minimax dual variational problems are formulated and usual duality theorems are established under convexity-concavity and pseudoconvexity-pseudoconcavity hypotheses respectively on the function <InlineEquation ID="Equ1"> <EquationSource Format="TEX"/> </InlineEquation> that appears in the two distinct dual pairs. Under an additional...</inlineequation>

In this paper, we establish a strong duality theorem for a pair of Mond–Weir type second-order nondifferentiable symmetric dual problems. This removes certain inconsistencies in some of the earlier results.

Wolfe and Mond-Weir type symmetric minimax dual variational problems are formulated and usual duality theorems are established under convexity-concavity and pseudoconvexity-pseudoconcavity hypotheses respectively on the function that appears in the two distinct dual pairs. Under an additional...

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,...