First-order methods for solving convex optimization problems have been at the forefront of
mathematical optimization in the last 20 years. The rapid development of this important class …

We introduce an inexact oracle model for variational inequalities with monotone operators,
propose a numerical method that solves such variational inequalities, and analyze its …

In this paper, we are motivated by two important applications: entropy-regularized optimal
transport problem and road or IP traffic demand matrix estimation by entropy model. Both of …

In this paper, we propose new first-order methods for minimization of a convex function on a
simple convex set. We assume that the objective function is a composite function given as a …

In this short paper, we describe natural logit population games dynamics that explain
equilibrium models of origin-destination matrix estimation and (stochastic) traffic assignment …

In this paper, we propose universal proximal mirror methods to solve the variational
inequality problem with Hölder-continuous operators in both deterministic and stochastic …

We introduce an inexact oracle model for variational inequalities (VI) with monotone
operator, propose a numerical method which solves such VI's and analyze its convergence …

In this paper, we consider resource allocation problem stated as a convex minimization
problem with linear constraints. To solve this problem, we use gradient and accelerated …

In this paper, we consider the application of several gradient methods to the traffic
assignment problem: we search equilibria in the stable dynamics model (Nesterov and De …

This chapter is devoted to the blackbox subgradient algorithms with the minimal
requirements for the storage of auxiliary results, which are necessary to execute these …