Primal-Dual Methods for Solving Infinite-Dimensional Games. - Pavel E. Dvurechensky; Yurii E. Nesterov; Vladimir G. Spokoiny (J. Optim. Theory Appl., 2015)

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)

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

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)

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)

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 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)

Generalized Self-concordant Hessian-barrier algorithms. - Pavel E. Dvurechensky; Mathias Staudigl; César A. Uribe (CoRR, 2019)

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

Self-Concordant Analysis of Frank-Wolfe Algorithms. - Pavel E. Dvurechensky; Petr Ostroukhov; Kamil Safin; Shimrit Shtern; Mathias Staudigl (ICML, 2020)

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

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

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)

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)

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

First-Order Methods for Convex Optimization. - Pavel E. Dvurechensky; Shimrit Shtern; Mathias Staudigl (EURO J. Comput. Optim., 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)

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)

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 conditional gradient homotopy method with applications to Semidefinite Programming. - Pavel E. Dvurechensky; Shimrit Shtern; Mathias Staudigl (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)

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)

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)

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

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)

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

Generalized self-concordant analysis of Frank-Wolfe algorithms. - Pavel E. Dvurechensky; Kamil Safin; Shimrit Shtern; Mathias Staudigl (Math. Program., 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)

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)

Analysis of Kernel Mirror Prox for Measure Optimization. - Pavel E. Dvurechensky; Jia-Jie Zhu (AISTATS, 2024)

Barrier Algorithms for Constrained Non-Convex Optimization. - Pavel E. Dvurechensky; Mathias Staudigl (ICML, 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)

Interaction-Force Transport Gradient Flows. - Egor Gladin; Pavel E. Dvurechenskii; Alexander Mielke; Jia-Jie Zhu (NeurIPS, 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)

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)

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)

Hessian barrier algorithms for non-convex conic optimization. - Pavel E. Dvurechensky; Mathias Staudigl (Math. Program., 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)