The nearest point problem (NPP), ie, finding the closest points between two disjoint convex
hulls, has two classical solutions, the Gilbert–Schlesinger–Kozinec (GSK) and Mitchell …

A convex polyhedron classifier that encloses the minority class using a combination of
hyperplanes is potentially effective in imbalanced classification. To construct an easy-to-use …

The geometric framework for binary data classification problems provides an intuitive
foundation for the comprehension and application of geometric optimization algorithms …

Термин математическая диагностика был введен ВФ Демьяновым в начале 2000-х
годов. Простейшая задача математической диагностики заключается в выяснении …

In this paper we will prove a linear convergence rate for the extension of the Mitchell, Dem׳
yanov and Malozemov (MDM) algorithm for solving the Nearest Point Problem (NPP). While …

The term “mathematical diagnostics” was introduced by VF Demyanov in the early 2000s.
The simplest problem of mathematical diagnostics is to determine the relative position of …

Resumen Support Vector Machines (SVMs) constitute one of the most successful paradigms
in Machine Learning nowadays. Their success stems from the fact that they are relatively …

The parametric-margin ν-support vector machine (par-ν-SVM) is a useful classifier in many
cases, especially when the noise is heteroscedastic. In this paper, the geometric …

In this paper we establish a framework for the convergence of two algorithms for solving the
Nearest Point Problem in Reduced Convex Hulls (RCH-NPP), namely the RCH-GSK …

Термин математическая диагностика был введен ВФ Демьяновым в начале 2000-х
годов. Простейшая задача математической диагностики заключается в выяснении …