66 citations · 450 across the 76 of their papers we have counts for
10 papers · 1 filter
Randomized gradient-free methods in convex optimization
Alexander Gasnikov, Darina Dvinskikh, Pavel Dvurechensky +3
This review presents modern gradient-free methods to solve convex optimization problems. By gradient-free methods, we mean those that use only (noisy) realizations of the objective…
Numerical Methods for Large-Scale Optimal Transport
Nazarii Tupitsa, Pavel Dvurechensky, Darina Dvinskikh +1
The optimal transport (OT) problem is a classical optimization problem having the form of linear programming. Machine learning applications put forward new computational challenges…
Exploiting higher-order derivatives in convex optimization methods
Dmitry Kamzolov, Alexander Gasnikov, Pavel Dvurechensky +2
Exploiting higher-order derivatives in convex optimization is known at least since 1970's. In each iteration higher-order (also called tensor) methods minimize a regularized Taylor…
A conditional gradient homotopy method with applications to Semidefinite Programming
Pavel Dvurechensky, Gabriele Iommazzo, Shimrit Shtern +1
We propose a new homotopy-based conditional gradient method for solving convex optimization problems with a large number of simple conic constraints. Instances of this template nat…
Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise
Eduard Gorbunov, Marina Danilova, David Dobre +3
Stochastic first-order methods such as Stochastic Extragradient (SEG) or Stochastic Gradient Descent-Ascent (SGDA) for solving smooth minimax problems and, more generally, variatio…
Decentralized Convex Optimization on Time-Varying Networks with Application to Wasserstein Barycenters
Olga Yufereva, Michael Persiianov, Pavel Dvurechensky +2
Inspired by recent advances in distributed algorithms for approximating Wasserstein barycenters, we propose a novel distributed algorithm for this problem. The main novelty is that…
Decentralized convex optimization under affine constraints for power systems control
Demyan Yarmoshik, Alexander Rogozin, Oleg. O. Khamisov +2
Modern power systems are now in continuous process of massive changes. Increased penetration of distributed generation, usage of energy storage and controllable demand require intr…
A General Framework for Distributed Partitioned Optimization
Savelii Chezhegov, Anton Novitskii, Alexander Rogozin +3
Decentralized optimization is widely used in large scale and privacy preserving machine learning and various distributed control and sensing systems. It is assumed that every agent…
An Approach for Non-Convex Uniformly Concave Structured Saddle Point Problem
Mohammad Alkousa, Alexander Gasnikov, Pavel Dvurechensky +2
Recently, saddle point problems have received much attention due to their powerful modeling capability for a lot of problems from diverse domains. Applications of these problems oc…
The Power of First-Order Smooth Optimization for Black-Box Non-Smooth Problems
Alexander Gasnikov, Anton Novitskii, Vasilii Novitskii +6
Gradient-free/zeroth-order methods for black-box convex optimization have been extensively studied in the last decade with the main focus on oracle calls complexity. In this paper,…