We propose an improved version of the SMO algorithm for training classification and
regression SVMs, based on a Conjugate Descent procedure. This new approach only …

Many important linear sparse models have at its core the Lasso problem, for which the
GLMNet algorithm is often considered as the current state of the art. Recently M. Jaggi has …

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

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 …

Onboard aircraft systems must frequently plan dynamically feasible paths or trajectories to
safely and quickly reach their goal position. Optimized B-splines are promising because they …

We study two important SVM variants: hard-margin SVM (for linearly separable cases) and
$\nu $-SVM (for linearly non-separable cases). We propose new algorithms from the …

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

We propose a conjugate descent procedure for the Frank–Wolfe algorithm with swap steps
for the Minimum Norm Problem that leads to a substantial decrease in the number of …

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 …

We study two important SVM variants: hard-margin SVM (for linearly separable cases) and
nu-SVM (for linearly non-separable cases). We propose new algorithms from the …