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

Building upon Gilbert's convergence proof of his algorithtm to solve the Minimum Norm
Problem, we establish a framework where a much simplified version of his proof allows us to …

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 …

Scaled Convex Hulls (SCHs) have been recently proposed by Liu et al. as the basis of a
method to build linear classifiers that, when extended to kernel settings, provides an …

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 …

МДМ-алгоритм ориентирован на нахождение ближайшей к началу координат точки из
выпуклой оболочки конечного числа заданных точек [1, 2, 3]. В докладе [4] предложено …

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

It is well known that the dual function value sequence generated by SMO has a linear
convergence rate when the kernel matrix is positive definite and sublinear convergence is …

In this paper we will describe a simple proof of a linear convergence rate for the MDM
algorithm that solves the Minimum Norm Problem (MNP). Linear convergence rates have …

1 Project Objectives The project Aprendizaje Automático y Aplicaciones (A3, Machine
Learning and Applications) is a joint project between a research group of the Instituto de …