Selected mathematical problems of traffic flow theory. - Alexander P. Buslaev; Alexander V. Gasnikov; Marina V. Yashina 001 (Int. J. Comput. Math., 2012)

Efficient randomized algorithms for PageRank problem. - Alexander V. Gasnikov; Denis Dmitriev (CoRR, 2014)

Fast Primal-Dual Gradient Method for Strongly Convex Minimization Problems with Linear Constraints. - Alexey Chernov; Pavel E. Dvurechensky; Alexander V. Gasnikov (DOOR, 2016)

Primal-Dual Method for Searching Equilibrium in Hierarchical Congestion Population Games. - Pavel E. Dvurechensky; Alexander V. Gasnikov; Evgenia Gasnikova; Sergey Matsievsky; Anton Rodomanov; Inna Usik (DOOR (Supplement), 2016)

Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods. - Lev Bogolubsky; Pavel E. Dvurechensky; Alexander V. Gasnikov; Gleb Gusev; Yurii E. Nesterov; Andrei M. Raigorodskii; Aleksey Tikhonov; Maksim Zhukovskii (NIPS, 2016)

Gradient-free proximal methods with inexact oracle for convex stochastic nonsmooth optimization problems on the simplex. - Alexander V. Gasnikov; Anastasia A. Lagunovskaya; Ilnura Usmanova; Fedor A. Fedorenko (Autom. Remote. Control., 2016)

Stochastic Intermediate Gradient Method for Convex Problems with Stochastic Inexact Oracle. - Pavel E. Dvurechensky; Alexander V. Gasnikov (J. Optim. Theory Appl., 2016)

Stochastic online optimization. Single-point and multi-point non-linear multi-armed bandits. Convex and strongly-convex case. - Alexander V. Gasnikov; Ekaterina A. Krymova; Anastasia A. Lagunovskaya; Ilnura Usmanova; Fedor A. Fedorenko (Autom. Remote. Control., 2017)

Randomized Similar Triangles Method: A Unifying Framework for Accelerated Randomized Optimization Methods (Coordinate Descent, Directional Search, Derivative-Free Method). - Pavel E. Dvurechensky; Alexander V. Gasnikov; Alexander Tiurin (CoRR, 2017)

Around power law for PageRank components in Buckley-Osthus model of web graph. - Alexander V. Gasnikov; Maksim Zhukovskii; Sergey Kim; Fedor Noskov; Stepan Plaunov; Daniil Smirnov (CoRR, 2017)

Optimal Algorithms for Distributed Optimization. - César A. Uribe; Soomin Lee; Alexander V. Gasnikov; Angelia Nedic (CoRR, 2017)

Distributed Computation of Wasserstein Barycenters Over Networks. - Cesar A. Uribe; Darina Dvinskikh; Pavel E. Dvurechensky; Alexander V. Gasnikov; Angelia Nedic (CDC, 2018)

Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm. - Pavel E. Dvurechensky; Alexander V. Gasnikov; Alexey Kroshnin (ICML, 2018)

Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters. - Pavel E. Dvurechenskii; Darina Dvinskikh; Alexander V. Gasnikov; César A. Uribe; Angelia Nedich (NeurIPS, 2018)

Gradient-Free Two-Point Methods for Solving Stochastic Nonsmooth Convex Optimization Problems with Small Non-Random Noises. - A. S. Bayandina; Alexander V. Gasnikov; Anastasia A. Lagunovskaya (Autom. Remote. Control., 2018)

On Primal and Dual Approaches for Distributed Stochastic Convex Optimization over Networks. - Darina Dvinskikh; Eduard Gorbunov; Alexander V. Gasnikov; Pavel E. Dvurechensky; César A. Uribe (CDC, 2019)

Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives. - Alexander V. Gasnikov; Pavel E. Dvurechensky; Eduard Gorbunov; Evgeniya A. Vorontsova; Daniil Selikhanovych; César A. Uribe; Bo Jiang 007; Haoyue Wang; Shuzhong Zhang; Sébastien Bubeck; Qijia Jiang; Yin Tat Lee; et al. (COLT, 2019)

Optimal Tensor Methods in Smooth Convex and Uniformly ConvexOptimization. - Alexander V. Gasnikov; Pavel E. Dvurechensky; Eduard Gorbunov; Evgeniya A. Vorontsova; Daniil Selikhanovych; César A. Uribe (COLT, 2019)

On the Complexity of Approximating Wasserstein Barycenters. - Alexey Kroshnin; Nazarii Tupitsa; Darina Dvinskikh; Pavel E. Dvurechensky; Alexander V. Gasnikov; Cesar A. Uribe (ICML, 2019)

Gradient Methods for Problems with Inexact Model of the Objective. - Fedor S. Stonyakin; Darina Dvinskikh; Pavel E. Dvurechensky; Alexey Kroshnin; Olesya Kuznetsova; Artem Agafonov; Alexander V. Gasnikov; Alexander Tyurin; César A. Uribe; Dmitry Pasechnyuk; Sergei Artamonov (MOTOR, 2019)

Accelerated Directional Search with Non-Euclidean Prox-Structure. - Evgeniya A. Vorontsova; Alexander V. Gasnikov; Eduard A. Gorbunov (Autom. Remote. Control., 2019)

Accelerated Gradient-Free Optimization Methods with a Non-Euclidean Proximal Operator. - Evgeniya A. Vorontsova; Alexander V. Gasnikov; Eduard A. Gorbunov; Pavel E. Dvurechenskii (Autom. Remote. Control., 2019)

On the Complexity of Approximating Wasserstein Barycenter. - Alexey Kroshnin; Darina Dvinskikh; Pavel E. Dvurechensky; Alexander V. Gasnikov; Nazarii Tupitsa; César A. Uribe (CoRR, 2019)

Accelerated Alternating Minimization. - Sergey Guminov; Pavel E. Dvurechensky; Alexander V. Gasnikov (CoRR, 2019)

A universal modification of the linear coupling method. - Sergey Guminov; Alexander V. Gasnikov; Anton Anikin 002; Alexander Gornov (Optim. Methods Softw., 2019)

Multimarginal Optimal Transport by Accelerated Alternating Minimization. - Nazarii Tupitsa; Pavel E. Dvurechensky; Alexander V. Gasnikov; César A. Uribe (CDC, 2020)

A Stable Alternative to Sinkhorn's Algorithm for Regularized Optimal Transport. - Pavel E. Dvurechensky; Alexander V. Gasnikov; Sergey Omelchenko; Alexander Tiurin (MOTOR, 2020)

Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping. - Eduard Gorbunov; Marina Danilova; Alexander V. Gasnikov (NeurIPS, 2020)

Optimal Combination of Tensor Optimization Methods. - Dmitry Kamzolov; Alexander V. Gasnikov; Pavel E. Dvurechensky (OPTIMA, 2020)

Penalty-Based Method for Decentralized Optimization over Time-Varying Graphs. - Alexander Rogozin; Alexander V. Gasnikov (OPTIMA, 2020)

Gradient-Free Methods for Saddle-Point Problem. - Aleksandr Beznosikov; Abdurakhmon Sadiev; Alexander V. Gasnikov (CoRR, 2020)

Stochastic Saddle-Point Optimization for Wasserstein Barycenters. - Daniil Tiapkin; Alexander V. Gasnikov; Pavel E. Dvurechensky (CoRR, 2020)

Zeroth-Order Algorithms for Smooth Saddle-Point Problems. - Abdurakhmon Sadiev; Aleksandr Beznosikov; Pavel E. Dvurechensky; Alexander V. Gasnikov (CoRR, 2020)

Local SGD for Saddle-Point Problems. - Aleksandr Beznosikov; Valentin Samokhin; Alexander V. Gasnikov (CoRR, 2020)

Recent Theoretical Advances in Non-Convex Optimization. - Marina Danilova; Pavel E. Dvurechensky; Alexander V. Gasnikov; Eduard Gorbunov; Sergey Guminov; Dmitry Kamzolov; Innokentiy Shibaev (CoRR, 2020)

Optimal Distributed Convex Optimization on Slowly Time-Varying Graphs. - Alexander Rogozin; César A. Uribe; Alexander V. Gasnikov; Nikolay Malkovsky; Angelia Nedic (IEEE Trans. Control. Netw. Syst., 2020)

An Accelerated Second-Order Method for Distributed Stochastic Optimization. - Artem Agafonov; Pavel E. Dvurechensky; Gesualdo Scutari; Alexander V. Gasnikov; Dmitry Kamzolov; Aleksandr Lukashevich; Amir Daneshmand (CDC, 2021)

An Accelerated Method For Decentralized Distributed Stochastic Optimization Over Time-Varying Graphs. - Alexander Rogozin; Mikhail Bochko; Pavel E. Dvurechensky; Alexander V. Gasnikov; Vladislav Lukoshkin (CDC, 2021)

Newton Method over Networks is Fast up to the Statistical Precision. - Amir Daneshmand; Gesualdo Scutari; Pavel E. Dvurechensky; Alexander V. Gasnikov (ICML, 2021)

On a Combination of Alternating Minimization and Nesterov's Momentum. - Sergey Guminov; Pavel E. Dvurechensky; Nazarii Tupitsa; Alexander V. Gasnikov (ICML, 2021)

ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. - Dmitry Kovalev; Egor Shulgin; Peter Richtárik; Alexander Rogozin; Alexander V. Gasnikov (ICML, 2021)

One-Point Gradient-Free Methods for Smooth and Non-smooth Saddle-Point Problems. - Aleksandr Beznosikov; Vasilii Novitskii; Alexander V. Gasnikov (MOTOR, 2021)

Convex Optimization with Inexact Gradients in Hilbert Space and Applications to Elliptic Inverse Problems. - Vladislav Matyukhin; Sergey Igorevich Kabanikhin; Maxim A. Shishlenin; Nikita S. Novikov; Artem Vasin; Alexander V. Gasnikov (MOTOR, 2021)

Distributed Saddle-Point Problems Under Data Similarity. - Aleksandr Beznosikov; Gesualdo Scutari; Alexander Rogozin; Alexander V. Gasnikov (NeurIPS, 2021)

Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks. - Dmitry Kovalev; Elnur Gasanov; Alexander V. Gasnikov; Peter Richtárik (NeurIPS, 2021)

Near-Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks. - Aleksandr Beznosikov; Alexander Rogozin; Dmitry Kovalev; Alexander V. Gasnikov (OPTIMA, 2021)

Adaptive Catalyst for Smooth Convex Optimization. - Anastasiya Ivanova; Dmitry Pasechnyuk; Dmitry Grishchenko; Egor Shulgin; Alexander V. Gasnikov; Vladislav Matyukhin (OPTIMA, 2021)

Towards Accelerated Rates for Distributed Optimization over Time-Varying Networks. - Alexander Rogozin; Vladislav Lukoshkin; Alexander V. Gasnikov; Dmitry Kovalev; Egor Shulgin (OPTIMA, 2021)

Solving Convex Min-Min Problems with Smoothness and Strong Convexity in One Group of Variables and Low Dimension in the Other. - Egor Gladin; Mohammad S. Alkousa; Alexander V. Gasnikov (Autom. Remote. Control., 2021)

Decentralized Distributed Optimization for Saddle Point Problems. - Alexander Rogozin; Aleksandr Beznosikov; Darina Dvinskikh; Dmitry Kovalev; Pavel E. Dvurechensky; Alexander V. Gasnikov (CoRR, 2021)

Convex optimization. - Evgeniya A. Vorontsova; Roland Hildebrand; Alexander V. Gasnikov; Fedor S. Stonyakin (CoRR, 2021)

Near-Optimal High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise. - Eduard Gorbunov; Marina Danilova; Innokentiy Shibaev; Pavel E. Dvurechensky; Alexander V. Gasnikov (CoRR, 2021)

Decentralized Personalized Federated Min-Max Problems. - Aleksandr Beznosikov; Vadim Sushko; Abdurakhmon Sadiev; Alexander V. Gasnikov (CoRR, 2021)

One-Point Gradient-Free Methods for Composite Optimization with Applications to Distributed Optimization. - Ivan Stepanov; Artyom Voronov; Aleksandr Beznosikov; Alexander V. Gasnikov (CoRR, 2021)

Distributed Saddle-Point Problems Under Similarity. - Aleksandr Beznosikov; Gesualdo Scutari; Alexander Rogozin; Alexander V. Gasnikov (CoRR, 2021)

An accelerated directional derivative method for smooth stochastic convex optimization. - Pavel E. Dvurechensky; Eduard Gorbunov; Alexander V. Gasnikov (Eur. J. Oper. Res., 2021)

Composite optimization for the resource allocation problem. - Anastasiya Ivanova; Pavel E. Dvurechensky; Alexander V. Gasnikov; Dmitry Kamzolov (Optim. Methods Softw., 2021)

Universal intermediate gradient method for convex problems with inexact oracle. - Dmitry Kamzolov; Pavel E. Dvurechensky; Alexander V. Gasnikov (Optim. Methods Softw., 2021)

Primal-dual accelerated gradient methods with small-dimensional relaxation oracle. - Yurii E. Nesterov; Alexander V. Gasnikov; Sergey Guminov; Pavel E. Dvurechensky (Optim. Methods Softw., 2021)

Inexact model: a framework for optimization and variational inequalities. - Fedor S. Stonyakin; Alexander Tyurin; Alexander V. Gasnikov; Pavel E. Dvurechensky; Artem Agafonov; Darina Dvinskikh; Mohammad S. Alkousa; Dmitry Pasechnyuk; Sergei Artamonov; Victoria V. Piskunova (Optim. Methods Softw., 2021)

A dual approach for optimal algorithms in distributed optimization over networks. - César A. Uribe; Soomin Lee; Alexander V. Gasnikov; Angelia Nedic (Optim. Methods Softw., 2021)

Acceleration in Distributed Optimization under Similarity. - Ye Tian 021; Gesualdo Scutari; Tianyu Cao 005; Alexander V. Gasnikov (AISTATS, 2022)

Primal-Dual Stochastic Mirror Descent for MDPs. - Daniil Tiapkin; Alexander V. Gasnikov (AISTATS, 2022)

The power of first-order smooth optimization for black-box non-smooth problems. - Alexander V. Gasnikov; Anton Novitskii; Vasilii Novitskii; Farshed Abdukhakimov; Dmitry Kamzolov; Aleksandr Beznosikov; Martin Takác 001; Pavel E. Dvurechensky; Bin Gu 001 (ICML, 2022)

Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. - Aleksandr Beznosikov; Pavel E. Dvurechensky; Anastasia Koloskova; Valentin Samokhin; Sebastian U. Stich; Alexander V. Gasnikov (NeurIPS, 2022)

Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees. - Aleksandr Beznosikov; Peter Richtárik; Michael Diskin; Max Ryabinin; Alexander V. Gasnikov (NeurIPS, 2022)

Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise. - Eduard Gorbunov; Marina Danilova; David Dobre; Pavel E. Dvurechenskii; Alexander V. Gasnikov; Gauthier Gidel (NeurIPS, 2022)

A Damped Newton Method Achieves Global $ mathcal O left( frac{1}{k^2} right)$ and Local Quadratic Convergence Rate. - Slavomír Hanzely; Dmitry Kamzolov; Dmitry Pasechnyuk; Alexander V. Gasnikov; Peter Richtárik; Martin Takác 001 (NeurIPS, 2022)

Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity. - Dmitry Kovalev; Aleksandr Beznosikov; Ekaterina Borodich; Alexander V. Gasnikov; Gesualdo Scutari (NeurIPS, 2022)

Optimal Algorithms for Decentralized Stochastic Variational Inequalities. - Dmitry Kovalev; Aleksandr Beznosikov; Abdurakhmon Sadiev; Michael Persiianov; Peter Richtárik; Alexander V. Gasnikov (NeurIPS, 2022)

The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization. - Dmitry Kovalev; Alexander V. Gasnikov (NeurIPS, 2022)

The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization. - Dmitry Kovalev; Alexander V. Gasnikov (NeurIPS, 2022)

Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling. - Dmitry Kovalev; Alexander V. Gasnikov; Peter Richtárik (NeurIPS, 2022)

Some Adaptive First-Order Methods for Variational Inequalities with Relatively Strongly Monotone Operators and Generalized Smoothness. - Seydamet S. Ablaev; Alexander A. Titov; Fedor S. Stonyakin; Mohammad S. Alkousa; Alexander V. Gasnikov (OPTIMA, 2022)

Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities. - Aleksandr Beznosikov; Alexander V. Gasnikov (OPTIMA, 2022)

Application of Attention Technique for Digital Pre-distortion. - Aleksandr Maslovskiy; Aleksandr Kunitsyn; Alexander V. Gasnikov (OPTIMA (2), 2022)

Decentralized Strongly-Convex Optimization with Affine Constraints: Primal and Dual Approaches. - Alexander Rogozin; Demyan Yarmoshik; Ksenia Kopylova; Alexander V. Gasnikov (OPTIMA (2), 2022)

Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity. - Dmitry Kovalev; Aleksandr Beznosikov; Ekaterina Borodich; Alexander V. Gasnikov; Gesualdo Scutari (CoRR, 2022)

On Scaled Methods for Saddle Point Problems. - Aleksandr Beznosikov; Aibek Alanov; Dmitry Kovalev; Martin Takác 001; Alexander V. Gasnikov (CoRR, 2022)

Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems - Survey. - Aleksandr Beznosikov; Boris T. Polyak; Eduard Gorbunov; Dmitry Kovalev; Alexander V. Gasnikov (CoRR, 2022)

SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities. - Aleksandr Beznosikov; Alexander V. Gasnikov (CoRR, 2022)

Accelerated variance-reduced methods for saddle-point problems. - Ekaterina Borodich; Vladislav Tominin; Yaroslav Tominin; Dmitry Kovalev; Alexander V. Gasnikov; Pavel E. Dvurechensky (EURO J. Comput. Optim., 2022)

Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization. - Pavel E. Dvurechensky; Dmitry Kamzolov; Aleksandr Lukashevich; Soomin Lee; Erik Ordentlich; César A. Uribe; Alexander V. Gasnikov (EURO J. Comput. Optim., 2022)

Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes. - Abdurakhmon Sadiev; Ekaterina Borodich; Aleksandr Beznosikov; Darina Dvinskikh; Saveliy Chezhegov; Rachael Tappenden; Martin Takác 001; Alexander V. Gasnikov (EURO J. Comput. Optim., 2022)

Oracle Complexity Separation in Convex Optimization. - Anastasiya Ivanova; Pavel E. Dvurechensky; Evgeniya A. Vorontsova; Dmitry Pasechnyuk; Alexander V. Gasnikov; Darina Dvinskikh; Alexander Tyurin (J. Optim. Theory Appl., 2022)

Generalized Mirror Prox Algorithm for Monotone Variational Inequalities: Universality and Inexact Oracle. - Fedor S. Stonyakin; Alexander V. Gasnikov; Pavel E. Dvurechensky; Alexander A. Titov; Mohammad S. Alkousa (J. Optim. Theory Appl., 2022)

Improved exploitation of higher order smoothness in derivative-free optimization. - Vasilii Novitskii; Alexander V. Gasnikov (Optim. Lett., 2022)

Zeroth-order methods for noisy Hölder-gradient functions. - Innokentiy Shibaev; Pavel E. Dvurechensky; Alexander V. Gasnikov (Optim. Lett., 2022)

Stochastic saddle-point optimization for the Wasserstein barycenter problem. - Daniil Tiapkin; Alexander V. Gasnikov; Pavel E. Dvurechensky (Optim. Lett., 2022)

Efficient numerical methods to solve sparse linear equations with application to PageRank. - Anton Anikin 002; Alexander V. Gasnikov; Alexander Gornov; Dmitry Kamzolov; Yury Maximov; Yurii E. Nesterov (Optim. Methods Softw., 2022)

An Accelerated Method for Derivative-Free Smooth Stochastic Convex Optimization. - Eduard Gorbunov; Pavel E. Dvurechensky; Alexander V. Gasnikov (SIAM J. Optim., 2022)

Algorithm for Constrained Markov Decision Process with Linear Convergence. - Egor Gladin; Maksim Lavrik-Karmazin; Karina Zainullina; Varvara Rudenko; Alexander V. Gasnikov; Martin Takác 001 (AISTATS, 2023)

Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks? - Dmitry Metelev; Alexander Rogozin; Dmitry Kovalev; Alexander V. Gasnikov (ICML, 2023)

High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance. - Abdurakhmon Sadiev; Marina Danilova; Eduard Gorbunov; Samuel Horváth; Gauthier Gidel; Pavel E. Dvurechensky; Alexander V. Gasnikov; Peter Richtárik (ICML, 2023)

First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities. - Aleksandr Beznosikov; Sergey Samsonov; Marina Sheshukova; Alexander V. Gasnikov; Alexey Naumov; Eric Moulines (NeurIPS, 2023)

Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities. - Aleksandr Beznosikov; Martin Takác 001; Alexander V. Gasnikov (NeurIPS, 2023)

Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance. - Nikita Kornilov; Ohad Shamir; Aleksandr V. Lobanov; Darina Dvinskikh; Alexander V. Gasnikov; Innokentiy Shibaev; Eduard Gorbunov; Samuel Horváth (NeurIPS, 2023)

Accelerated Zero-Order SGD Method for Solving the Black Box Optimization Problem Under "Overparametrization" Condition. - Aleksandr V. Lobanov; Alexander V. Gasnikov (OPTIMA, 2023)

Algorithms for Euclidean-Regularised Optimal Transport. - Dmitry Pasechnyuk; Michael Persiianov; Pavel E. Dvurechensky; Alexander V. Gasnikov (OPTIMA, 2023)

Real Acceleration of Communication Process in Distributed Algorithms with Compression. - Svetlana Tkachenko; Artem Andreev; Aleksandr Beznosikov; Alexander V. Gasnikov (OPTIMA, 2023)

Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities. - Aleksandr Beznosikov; Alexander V. Gasnikov (CoRR, 2023)

Accelerated gradient methods with absolute and relative noise in the gradient. - Artem Vasin; Alexander V. Gasnikov; Pavel E. Dvurechensky; Vladimir G. Spokoiny (Optim. Methods Softw., 2023)

Accelerated methods for weakly-quasi-convex optimization problems. - Sergey Guminov; Alexander V. Gasnikov; Ilya A. Kuruzov (Comput. Manag. Sci., 2023)

Gradient-free methods for non-smooth convex stochastic optimization with heavy-tailed noise on convex compact. - Nikita Kornilov; Alexander V. Gasnikov; Pavel E. Dvurechensky; Darina Dvinskikh (Comput. Manag. Sci., 2023)

Non-smooth setting of stochastic decentralized convex optimization problem over time-varying Graphs. - Aleksandr V. Lobanov; Andrew Veprikov; Georgiy Konin; Aleksandr Beznosikov; Alexander V. Gasnikov; Dmitry Kovalev (Comput. Manag. Sci., 2023)

On Accelerated Coordinate Descent Methods for Searching Equilibria in Two-Stage Transportation Equilibrium Traffic Flow Distribution Model. - N. A. Il'tyakov; M. A. Obozov; I. M. Dyshlevski; Demyan Yarmoshik; M. B. Kubentaeva; Alexander V. Gasnikov; Evgenia Gasnikova (Program. Comput. Softw., 2023)

Decentralized Conditional Gradient Method on Time-Varying Graphs. - R. A. Vedernikov; Alexander Rogozin; Alexander V. Gasnikov (Program. Comput. Softw., 2023)

Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases. - Ruslan Nazykov; Aleksandr Shestakov; Vladimir Solodkin; Aleksandr Beznosikov; Gauthier Gidel; Alexander V. Gasnikov (AISTATS, 2024)

Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems. - Nikita Puchkin; Eduard Gorbunov; Nikolay Kutuzov; Alexander V. Gasnikov (AISTATS, 2024)

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness. - Artem Agafonov; Dmitry Kamzolov; Alexander V. Gasnikov; Ali Kavis; Kimon Antonakopoulos; Volkan Cevher; Martin Takác 001 (ICLR, 2024)

High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise. - Eduard Gorbunov; Abdurakhmon Sadiev; Marina Danilova; Samuel Horváth; Gauthier Gidel; Pavel E. Dvurechensky; Alexander V. Gasnikov; Peter Richtárik (ICML, 2024)

Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations. - Artem Agafonov; Petr Ostroukhov; Roman Mozhaev; Konstantin Yakovlev; Eduard Gorbunov; Martin Takác 001; Alexander V. Gasnikov; Dmitry Kamzolov (NeurIPS, 2024)

Optimal Flow Matching: Learning Straight Trajectories in Just One Step. - Nikita Kornilov; Petr Mokrov; Alexander V. Gasnikov; Alexander Korotin (NeurIPS, 2024)

Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks. - Dmitry Kovalev; Ekaterina Borodich; Alexander V. Gasnikov; Dmitrii Feoktistov (NeurIPS, 2024)

Achieving Linear Convergence with Parameter-Free Algorithms in Decentralized Optimization. - Ilya A. Kuruzov; Gesualdo Scutari; Alexander V. Gasnikov (NeurIPS, 2024)

Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values. - Aleksandr V. Lobanov; Alexander V. Gasnikov; Andrey Krasnov (NeurIPS, 2024)

Nesterov's Method of Dichotomy via Order Oracle: The Problem of Optimizing a Two-Variable Function on a Square. - Boris Chervonenkis; Andrei Krasnov; Alexander V. Gasnikov; Aleksandr V. Lobanov (OPTIMA, 2024)

An Equilibrium Dynamic Traffic Assignment Model with Linear Programming Formulation. - Victoria Guseva; Ilya Sklonin; Irina Podlipnova; Demyan Yarmoshik; Alexander V. Gasnikov (OPTIMA, 2024)

Activations and Gradients Compression for Model-Parallel Training. - Mikhail Rudakov; Aleksandr Beznosikov; Yaroslav Kholodov; Alexander V. Gasnikov (CoRR, 2024)

Optimal Data Splitting in Distributed Optimization for Machine Learning. - Daniil Medyakov; Gleb Molodtsov; Aleksandr Beznosikov; Alexander V. Gasnikov (CoRR, 2024)

AdaBatchGrad: Combining Adaptive Batch Size and Adaptive Step Size. - Petr Ostroukhov; Aigerim Zhumabayeva; Chulu Xiang; Alexander V. Gasnikov; Martin Takác 001; Dmitry Kamzolov (CoRR, 2024)

Optimal Flow Matching: Learning Straight Trajectories in Just One Step. - Nikita Kornilov; Alexander V. Gasnikov; Alexander Korotin (CoRR, 2024)

Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive Learning. - Andrei Semenov; Vladimir Ivanov; Aleksandr Beznosikov; Alexander V. Gasnikov (CoRR, 2024)

Local Methods with Adaptivity via Scaling. - Saveliy Chezhegov; Sergey Skorik; Nikolas Khachaturov; Danil Shalagin; Aram Avetisyan; Aleksandr Beznosikov; Martin Takác 001; Yaroslav Kholodov; Alexander V. Gasnikov (CoRR, 2024)

Gradient Clipping Improves AdaGrad when the Noise Is Heavy-Tailed. - Saveliy Chezhegov; Yaroslav Klyukin; Andrei Semenov; Aleksandr Beznosikov; Alexander V. Gasnikov; Samuel Horváth; Martin Takác 001; Eduard Gorbunov (CoRR, 2024)

Accelerated zero-order SGD under high-order smoothness and overparameterized regime. - Georgii Bychkov; Darina Dvinskikh; Anastasia Antsiferova; Alexander V. Gasnikov; Aleksandr V. Lobanov (CoRR, 2024)

Inexact tensor methods and their application to stochastic convex optimization. - Artem Agafonov; Dmitry Kamzolov; Pavel E. Dvurechensky; Alexander V. Gasnikov; Martin Takác 001 (Optim. Methods Softw., 2024)

Near-optimal tensor methods for minimizing the gradient norm of convex functions and accelerated primal-dual tensor methods. - Pavel E. Dvurechensky; Petr Ostroukhov; Alexander V. Gasnikov; César A. Uribe; Anastasiya Ivanova (Optim. Methods Softw., 2024)

Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed bandits. - Yuriy Dorn; Nikita Kornilov; Nikolay Kutuzov; Alexander Nazin; Eduard Gorbunov; Alexander V. Gasnikov (Comput. Manag. Sci., 2024)

Primal-dual gradient methods for searching network equilibria in combined models with nested choice structure and capacity constraints. - Meruza Kubentayeva; Demyan Yarmoshik; Michael Persiianov; Alexey Kroshnin; Ekaterina Kotliarova; Nazarii Tupitsa; Dmitry Pasechnyuk; Alexander V. Gasnikov; Vladimir Shvetsov; Leonid Baryshev; Alexey Shurupov (Comput. Manag. Sci., 2024)

Decentralized optimization over slowly time-varying graphs: algorithms and lower bounds. - Dmitry Metelev; Aleksandr Beznosikov; Alexander Rogozin; Alexander V. Gasnikov; Anton V. Proskurnikov (Comput. Manag. Sci., 2024)

Decentralized saddle-point problems with different constants of strong convexity and strong concavity. - Dmitry Metelev; Alexander Rogozin; Alexander V. Gasnikov; Dmitry Kovalev (Comput. Manag. Sci., 2024)

Preconditioning meets biased compression for efficient distributed optimization. - Vitali Pirau; Aleksandr Beznosikov; Martin Takác 001; Vladislav Matyukhin; Alexander V. Gasnikov (Comput. Manag. Sci., 2024)

Decentralized optimization with affine constraints over time-varying networks. - Demyan Yarmoshik; Alexander Rogozin; Alexander V. Gasnikov (Comput. Manag. Sci., 2024)

Decentralized convex optimization on time-varying networks with application to Wasserstein barycenters. - Olga Yufereva; Michael Persiianov; Pavel E. Dvurechensky; Alexander V. Gasnikov; Dmitry Kovalev (Comput. Manag. Sci., 2024)

High-Probability Complexity Bounds for Non-smooth Stochastic Convex Optimization with Heavy-Tailed Noise. - Eduard Gorbunov; Marina Danilova; Innokentiy Shibaev; Pavel E. Dvurechensky; Alexander V. Gasnikov (J. Optim. Theory Appl., 2024)

The "Black-Box" Optimization Problem: Zero-Order Accelerated Stochastic Method via Kernel Approximation. - Aleksandr V. Lobanov; Nail Bashirov; Alexander V. Gasnikov (J. Optim. Theory Appl., 2024)

OPTAMI: Global Superlinear Convergence of High-order Methods. - Dmitry Kamzolov; Artem Agafonov; Dmitry Pasechnyuk; Alexander V. Gasnikov; Martin Takác 001 (ICLR, 2025)

An Optimal Algorithm for Strongly Convex Min-Min Optimization. - Dmitry Kovalev; Alexander V. Gasnikov; Grigory Malinovsky (UAI, 2025)

Decentralised convex optimisation with probability-proportional-to-size quantization. - Dmitry Pasechnyuk; Pavel E. Dvurechensky; César A. Uribe; Alexander V. Gasnikov (EURO J. Comput. Optim., 2025)

Accuracy Certificates for Convex Minimization with Inexact Oracle. - Egor Gladin; Alexander V. Gasnikov; Pavel E. Dvurechensky (J. Optim. Theory Appl., 2025)

Sign Operator for Coping with Heavy-Tailed Noise: High Probability Convergence Bounds with Extensions to Distributed Optimization and Comparison Oracle. - Nikita Kornilov; Philip Zmushko; Andrei Semenov; Alexander V. Gasnikov; Aleksandr Beznosikov (CoRR, 2025)

Intermediate Gradient Methods with Relative Inexactness. - Nikita Kornilov; Mohammad S. Alkousa; Eduard Gorbunov; Fedor S. Stonyakin; Pavel E. Dvurechensky; Alexander V. Gasnikov (J. Optim. Theory Appl., 2025)