Kernel methods and support vector machines (SVMs) serve as cornerstones in modern machine learning, offering robust techniques for both classification and regression tasks. At their core, kernel ...

In this paper, we propose a kernel-free semi-supervised quadratic surface support vector machine model for binary classification. The model is formulated as a mixed-integer programming problem, which ...

Support Vector Machines (SVMs) are a versatile and powerful machine learning algorithm that has gained significant popularity for solving classification and regression problems. They have been ...

The Journal of the Operational Research Society, Vol. 60, No. 8, Data Mining and Operational Research: Techniques and Applications (Aug., 2009), pp. 1116-1122 (7 pages) The paper presents a novel ...