Pavel E. Dvurechensky

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 66

Top Topics

Semidefinite Program

Variational Inequalities

Optimization Methods

Top Venues

Optim. Methods Softw.

Publications

Pavel E. Dvurechensky, Jia-Jie Zhu
Analysis of Kernel Mirror Prox for Measure Optimization. AISTATS (2024)
Olga Yufereva, Michael Persiianov, Pavel E. Dvurechensky, Alexander V. Gasnikov, Dmitry Kovalev
Decentralized convex optimization on time-varying networks with application to Wasserstein barycenters. Comput. Manag. Sci. 21 (1) (2024)
Egor Gladin, Pavel E. Dvurechensky, Alexander Mielke, Jia-Jie Zhu
Interaction-Force Transport Gradient Flows. CoRR (2024)
Pavel E. Dvurechensky, Jia-Jie Zhu
Analysis of Kernel Mirror Prox for Measure Optimization. CoRR (2024)
Artem Agafonov, Dmitry Kamzolov, Pavel E. Dvurechensky, Alexander V. Gasnikov, Martin Takác
Inexact tensor methods and their application to stochastic convex optimization. Optim. Methods Softw. 39 (1) (2024)
Nikita Kornilov, Alexander V. Gasnikov, Pavel E. Dvurechensky, Darina Dvinskikh
Gradient-free methods for non-smooth convex stochastic optimization with heavy-tailed noise on convex compact. Comput. Manag. Sci. 20 (1) (2023)
Pavel E. Dvurechensky, Kamil Safin, Shimrit Shtern, Mathias Staudigl
Generalized self-concordant analysis of Frank-Wolfe algorithms. Math. Program. 198 (1) (2023)
Dmitry Pasechnyuk, Michael Persiianov, Pavel E. Dvurechensky, Alexander V. Gasnikov
Algorithms for Euclidean-Regularised Optimal Transport. OPTIMA (2023)
Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik
High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance. ICML (2023)
Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik
High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise. CoRR (2023)
Artem Vasin, Alexander V. Gasnikov, Pavel E. Dvurechensky, Vladimir G. Spokoiny
Accelerated gradient methods with absolute and relative noise in the gradient. Optim. Methods Softw. 38 (6) (2023)
Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik
High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance. CoRR (2023)
Aleksandr Beznosikov, Pavel E. Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U. Stich, Alexander V. Gasnikov
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. NeurIPS (2022)
Innokentiy Shibaev, Pavel E. Dvurechensky, Alexander V. Gasnikov
Zeroth-order methods for noisy Hölder-gradient functions. Optim. Lett. 16 (7) (2022)
Anastasiya Ivanova, Pavel E. Dvurechensky, Evgeniya A. Vorontsova, Dmitry Pasechnyuk, Alexander V. Gasnikov, Darina Dvinskikh, Alexander Tyurin
Oracle Complexity Separation in Convex Optimization. J. Optim. Theory Appl. 193 (1) (2022)
Pavel E. Dvurechensky, Shimrit Shtern, Mathias Staudigl
A conditional gradient homotopy method with applications to Semidefinite Programming. CoRR (2022)
Pavel E. Dvurechensky, Dmitry Kamzolov, Aleksandr Lukashevich, Soomin Lee, Erik Ordentlich, César A. Uribe, Alexander V. Gasnikov
Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization. EURO J. Comput. Optim. 10 (2022)
Eduard Gorbunov, Pavel E. Dvurechensky, Alexander V. Gasnikov
An Accelerated Method for Derivative-Free Smooth Stochastic Convex Optimization. SIAM J. Optim. 32 (2) (2022)
Eduard Gorbunov, Marina Danilova, David Dobre, Pavel E. Dvurechensky, Alexander V. Gasnikov, Gauthier Gidel
Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise. CoRR (2022)
Daniil Tiapkin, Alexander V. Gasnikov, Pavel E. Dvurechensky
Stochastic saddle-point optimization for the Wasserstein barycenter problem. Optim. Lett. 16 (7) (2022)
Alexander V. Gasnikov, Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takác, Pavel E. Dvurechensky, Bin Gu
The power of first-order smooth optimization for black-box non-smooth problems. ICML (2022)
Ekaterina Borodich, Vladislav Tominin, Yaroslav Tominin, Dmitry Kovalev, Alexander V. Gasnikov, Pavel E. Dvurechensky
Accelerated variance-reduced methods for saddle-point problems. EURO J. Comput. Optim. 10 (2022)
Fedor S. Stonyakin, Alexander V. Gasnikov, Pavel E. Dvurechensky, Alexander A. Titov, Mohammad S. Alkousa
Generalized Mirror Prox Algorithm for Monotone Variational Inequalities: Universality and Inexact Oracle. J. Optim. Theory Appl. 194 (3) (2022)
Amir Daneshmand, Gesualdo Scutari, Pavel E. Dvurechensky, Alexander V. Gasnikov
Newton Method over Networks is Fast up to the Statistical Precision. ICML (2021)
Pavel E. Dvurechensky, Mathias Staudigl, Shimrit Shtern
First-Order Methods for Convex Optimization. CoRR (2021)
Alexander Rogozin, Mikhail Bochko, Pavel E. Dvurechensky, Alexander V. Gasnikov, Vladislav Lukoshkin
An Accelerated Method For Decentralized Distributed Stochastic Optimization Over Time-Varying Graphs. CDC (2021)
Aleksandr Beznosikov, Pavel E. Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U. Stich, Alexander V. Gasnikov
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. CoRR (2021)
Artem Agafonov, Pavel E. Dvurechensky, Gesualdo Scutari, Alexander V. Gasnikov, Dmitry Kamzolov, Aleksandr Lukashevich, Amir Daneshmand
An Accelerated Second-Order Method for Distributed Stochastic Optimization. CDC (2021)
Yurii E. Nesterov, Alexander V. Gasnikov, Sergey Guminov, Pavel E. Dvurechensky
Primal-dual accelerated gradient methods with small-dimensional relaxation oracle. Optim. Methods Softw. 36 (4) (2021)
Dmitry Kamzolov, Pavel E. Dvurechensky, Alexander V. Gasnikov
Universal intermediate gradient method for convex problems with inexact oracle. Optim. Methods Softw. 36 (6) (2021)
Sergey Guminov, Pavel E. Dvurechensky, Nazarii Tupitsa, Alexander V. Gasnikov
On a Combination of Alternating Minimization and Nesterov's Momentum. ICML (2021)
Alexander Rogozin, Aleksandr Beznosikov, Darina Dvinskikh, Dmitry Kovalev, Pavel E. Dvurechensky, Alexander V. Gasnikov
Decentralized Distributed Optimization for Saddle Point Problems. CoRR (2021)
Eduard A. Gorbunov, Marina Danilova, Innokentiy Shibaev, Pavel E. Dvurechensky, Alexander V. Gasnikov
Near-Optimal High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise. CoRR (2021)
Pavel E. Dvurechensky, Eduard A. Gorbunov, Alexander V. Gasnikov
An accelerated directional derivative method for smooth stochastic convex optimization. Eur. J. Oper. Res. 290 (2) (2021)
Pavel E. Dvurechensky, Shimrit Shtern, Mathias Staudigl
First-Order Methods for Convex Optimization. EURO J. Comput. Optim. 9 (2021)
Amir Daneshmand, Gesualdo Scutari, Pavel E. Dvurechensky, Alexander V. Gasnikov
Newton Method over Networks is Fast up to the Statistical Precision. CoRR (2021)
Anastasiya Ivanova, Pavel E. Dvurechensky, Alexander V. Gasnikov, Dmitry Kamzolov
Composite optimization for the resource allocation problem. Optim. Methods Softw. 36 (4) (2021)
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
Inexact model: a framework for optimization and variational inequalities. Optim. Methods Softw. 36 (6) (2021)
Nazarii Tupitsa, Pavel E. Dvurechensky, Alexander V. Gasnikov, César A. Uribe
Multimarginal Optimal Transport by Accelerated Alternating Minimization. CDC (2020)
Marina Danilova, Pavel E. Dvurechensky, Alexander V. Gasnikov, Eduard A. Gorbunov, Sergey Guminov, Dmitry Kamzolov, Innokentiy Shibaev
Recent Theoretical Advances in Non-Convex Optimization. CoRR (2020)
Pavel E. Dvurechensky, Shimrit Shtern, Mathias Staudigl, Petr Ostroukhov, Kamil Safin
Self-concordant analysis of Frank-Wolfe algorithms. CoRR (2020)
Abdurakhmon Sadiev, Aleksandr Beznosikov, Pavel E. Dvurechensky, Alexander V. Gasnikov
Zeroth-Order Algorithms for Smooth Saddle-Point Problems. CoRR (2020)
Pavel E. Dvurechensky, Petr Ostroukhov, Kamil Safin, Shimrit Shtern, Mathias Staudigl
Self-Concordant Analysis of Frank-Wolfe Algorithms. ICML (2020)
Pavel E. Dvurechensky, Alexander V. Gasnikov, Sergey Omelchenko, Alexander Tiurin
A Stable Alternative to Sinkhorn's Algorithm for Regularized Optimal Transport. MOTOR (2020)
Dmitry Kamzolov, Alexander V. Gasnikov, Pavel E. Dvurechensky
Optimal Combination of Tensor Optimization Methods. OPTIMA (2020)
Daniil Tiapkin, Alexander V. Gasnikov, Pavel E. Dvurechensky
Stochastic Saddle-Point Optimization for Wasserstein Barycenters. CoRR (2020)
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
Gradient Methods for Problems with Inexact Model of the Objective. MOTOR (2019)
Alexey Kroshnin, Nazarii Tupitsa, Darina Dvinskikh, Pavel E. Dvurechensky, Alexander V. Gasnikov, Cesar A. Uribe
On the Complexity of Approximating Wasserstein Barycenters. ICML (2019)
Alexander V. Gasnikov, Pavel E. Dvurechensky, Eduard A. Gorbunov, Evgeniya A. Vorontsova, Daniil Selikhanovych, César A. Uribe, Bo Jiang, Haoyue Wang, Shuzhong Zhang, Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives. COLT (2019)
Sergey Guminov, Pavel E. Dvurechensky, Alexander V. Gasnikov
Accelerated Alternating Minimization. CoRR (2019)
Darina Dvinskikh, Eduard A. Gorbunov, Alexander V. Gasnikov, Pavel E. Dvurechensky, César A. Uribe
On Primal and Dual Approaches for Distributed Stochastic Convex Optimization over Networks. CDC (2019)
Alexander V. Gasnikov, Pavel E. Dvurechensky, Eduard A. Gorbunov, Evgeniya A. Vorontsova, Daniil Selikhanovych, César A. Uribe
Optimal Tensor Methods in Smooth Convex and Uniformly ConvexOptimization. COLT (2019)
Alexey Kroshnin, Darina Dvinskikh, Pavel E. Dvurechensky, Alexander V. Gasnikov, Nazarii Tupitsa, César A. Uribe
On the Complexity of Approximating Wasserstein Barycenter. CoRR (2019)
Pavel E. Dvurechensky, Mathias Staudigl, César A. Uribe
Generalized Self-concordant Hessian-barrier algorithms. CoRR (2019)
Pavel E. Dvurechensky, Alexander V. Gasnikov, Alexey Kroshnin
Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm. ICML (2018)
Pavel E. Dvurechensky, Alexander V. Gasnikov, Eduard A. Gorbunov
An Accelerated Method for Derivative-Free Smooth Stochastic Convex Optimization. CoRR (2018)
Cesar A. Uribe, Darina Dvinskikh, Pavel E. Dvurechensky, Alexander V. Gasnikov, Angelia Nedic
Distributed Computation of Wasserstein Barycenters Over Networks. CDC (2018)
Pavel E. Dvurechensky, Darina Dvinskikh, Alexander V. Gasnikov, César A. Uribe, Angelia Nedic
Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters. CoRR (2018)
Pavel E. Dvurechensky, Alexander V. Gasnikov, Eduard A. Gorbunov
An Accelerated Directional Derivative Method for Smooth Stochastic Convex Optimization. CoRR (2018)
Pavel E. Dvurechensky, Alexander V. Gasnikov, Alexey Kroshnin
Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm. CoRR (2018)
César A. Uribe, Darina Dvinskikh, Pavel E. Dvurechensky, Alexander V. Gasnikov, Angelia Nedic
Distributed Computation of Wasserstein Barycenters over Networks. CoRR (2018)
Pavel E. Dvurechensky, Alexander V. Gasnikov, Alexander Tiurin
Randomized Similar Triangles Method: A Unifying Framework for Accelerated Randomized Optimization Methods (Coordinate Descent, Directional Search, Derivative-Free Method). CoRR (2017)
Lev Bogolubsky, Pavel E. Dvurechensky, Alexander V. Gasnikov, Gleb Gusev, Yurii E. Nesterov, Andrei M. Raigorodskii, Aleksey Tikhonov, Maksim Zhukovskii
Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods. NIPS (2016)
Pavel E. Dvurechensky, Alexander V. Gasnikov
Stochastic Intermediate Gradient Method for Convex Problems with Stochastic Inexact Oracle. J. Optim. Theory Appl. 171 (1) (2016)
Alexey Chernov, Pavel E. Dvurechensky, Alexander V. Gasnikov
Fast Primal-Dual Gradient Method for Strongly Convex Minimization Problems with Linear Constraints. DOOR (2016)
Pavel E. Dvurechensky, Alexander V. Gasnikov, Evgenia Gasnikova, Sergey Matsievsky, Anton Rodomanov, Inna Usik
Primal-Dual Method for Searching Equilibrium in Hierarchical Congestion Population Games. DOOR (Supplement) (2016)
Pavel E. Dvurechensky, Yurii E. Nesterov, Vladimir G. Spokoiny
Primal-Dual Methods for Solving Infinite-Dimensional Games. J. Optim. Theory Appl. 166 (1) (2015)