Gasnikov Alexander Vladimirovich

Doctor of Computer Sciences (Habilitation), Professor

Head of the Laboratory of Mathematical Methods of Optimization, Head of the Department of Mathematical Foundations of Control

Citation statistics: 7391, since 2019 — 5660
h-index: 41, since 2019 — 38
i10-index: 178, since 2019 — 142
Date of Birth: September 2, 1983

Education

2006 — Moscow Institute of Physics and Technology, Department of Control and Applied Mathematics, Moscow, Russia

2007 — Candidate of Computer Sciences (PhD) in Partial Differential Equations, Thesis: “Asymptotic in time behavior of solution of Cauchy problem for conservation law with nonlinear divergent viscosity”, supervisor prof. A.A. Shananin, Moscow Institute of Physics and Technology, Moscow, Russia

2011 — Associate Professor at the Department of Mathematical Foundations of Control

2016 — Doctor of Computer Sciences (Habilitation) in Mathematical Modelling and Numerical methods of Convex Optimization, Doctoral Thesis: “Searching equilibriums in large transport networks”, supervisors prof. A.A. Shananin and prof. Yu.E. Nesterov

Work Experience

since August 2024 — Scientific Director of the Museum Space on the territory of the Sirius Concert Center

since 2024 — leading researcher at the Department of Mathematical Foundations of Artificial Intelligence MIAN RAS

since February 2024 — member of the Scientific Council of the AI Alliance Russia

since November 2023 — Rector of the Innopolis University

since August 2023 — Head of the Laboratory of Multi-scale Neurodynamics for Smart Systems of Skoltech

since 2023 — Chief Researcher of Skoltech

since 2023 — Head of Laboratory No. 10 of the IPPI RAS of Mathematical Foundations of Machine Learning

since 2023 — Member of the Editorial Board of the Siberian Journal of Industrial Mathematics

since 2023 — member of the Editorial Board of the Journal of Computational Mathematics and Mathematical Physics

since 2022 — Member of the Editorial board of the Journal of Optimization Theory and Applications — Q1 (one of the world's leading journals on numerical optimization methods)

since 2022 — Academic head of the PMF direction at the School of FPMI

Since 2022 — Head of the Laboratory of Mathematical Optimization Methods, Moscow Institute of Physics and Technology

since 2022 — Head of Department of Control and Applied Mathematics, Moscow Institute of Physics and Technology

since 2021 — Head of the group in the AI Center of the Institute of System Programming of the Russian Academy of Sciences 

since 2020 — Professor, Moscow Institute of Physics and Technology (State University)

since 2020 — Professor, Faculty of Computer Science, Higher School of Economics

since 2019 — Head of the group at Huawei project. Russia, Moscow

since 2016 — Member of the Editorial Board of the Siberian Journal of Computational Mathematics

Since 2015 — Lead researcher at IITP RAS (Institute for Information Transmission Problems of Russian Academy of Science), Moscow, Russia

2015-2020 — Professor at the HSE (High School Economics), Computer Science Department, Moscow, Russia

2011-2020 — Professor at MIPT (Moscow Institute of Physics and Technology), Department of Control and Applied Mathematics

Research Interests

Mathematical Modeling of Traffic Flows

Optimization (Huge-Scale, Distributed and Parallel, Stochastic, Online)

Learning from optimization point of view

Research Projects and Grants

RFBR 18-29-03071 "Big Data solutions for modeling, analysis and optimization of transport processes" (2018-2021) — performer

RFBR 18-31-20005 "Development of general principles for the construction and analysis of the convergence rate of numerical optimization methods based on the concept of the objective function model" (2018-2020) — Head

RFBR 19-31-51001 Scientific Mentoring "Distributed and parallel algorithms for solving data analysis problems" (2019-2021) — Head

RFBR 19-31-90062 Graduate students "A unified view on randomized numerical methods for solving convex optimization problems" (2019-2021) — Supervisor

RFBR 19-31-90170 Postgraduate students "Search for equilibria in transport networks using direct-dual accelerated methods with auxiliary one—dimensional optimization" (2019-2021) — Head

RNF 17-11-01027 Algorithmic optimization for problems with a large number of variables (2017-2019) — participant

RNF 18-71-10108 Optimal Transport: Numerical Methods and Applications to Data Analysis (2018-2021) — Participant

State Task No. 075-00337-20-03 "Development of effective algorithms for solving large—size optimization problems" (2020-2023) - performer

RFBR No. 19-31-51001 Scientific mentoring "Distributed and parallel algorithms for solving data analysis problems" (2020-2021) — Head

RNF 21-71-30005 Development of numerical optimization methods in applications to control problems, inverse problems and training (2021-2024) — main performer

RPF 23-11-00229 Development of efficient distributed algorithms for solving optimization problems (2023-2025)— head

Awards and Recognitions

Winner of the Yahoo Award for 2019

Winner of the Ilya Segalovich Award (Yandex) for 2020

Winner of the Moscow Government Prize for 2020

Winner of the Talent Funding Award by the Institute of Strategic Research (China) for 2023

Defended dissertations

Alkousa Mohammad, "Numerical Methods for Non-Smooth Convex Optimization Problems with Functional Constraints" (11.06.2020). Candidate of Physical and Mathematical Sciences.

Tyurin Alexander Igorevich, "Development of a method for solving structural optimization problems" (19.11.2020). PhD Candidate in Computer Science. 

Dvurechensky Pavel Evgenievich, "Numerical methods in large-scale optimization: inexact oracle and primal-dual analysis" (28.12.2020). Doctor of Computer Science.

Kamzolov Dmitry Igorevich, "Acceleration of Tensor Methods and Their Optimal Combination" (29.12.2020). Candidate of Physical and Mathematical Sciences.

Gorbunov Eduard Alexandrovich, "Distributed and Stochastic Optimization Methods with Gradient Compression and Local Steps" (23.12.2021). Candidate of Physical and Mathematical Sciences.

Omelchenko Sergey Sergeevich, "Численные методы решения задач выпуклой оптимизации больших размеров, имеющих специальную структуру" (23.12.2021). Candidate of Physical and Mathematical Sciences.

Kotlyarova Ekaterina Vladimirovna, "Поиск равновесия в многостадийных транспортных моделях"(15.12.2022). Candidate of Physical and Mathematical Sciences.

Matyukhin Vladislav Vyacheslavovich, «Ускоренный метаалгоритм и его приложения» (22.12.2022). Candidate of Physical and Mathematical Sciences.

Dorn Yuri Vladimirovich, «Модель Нестерова-де Пальмы и ее применение в задачах макроскопического моделирования транспортных потоков» (22.12.2022). Candidate of Technical Sciences.

Makarenko Dmitry Vladimirovich, «Разработка численных методов решения задач оптимизации при ослабленных условиях гладкости» (22.12.2022). Candidate of Physical and Mathematical Sciences.

Titov Alexander Alexandrovich, «Методы оптимизации для негладких задач в пространствах больших размерностей» (27.06.2023). PhD Candidate in Computer Science.

Beznosikov Alexander Nikolaevich, «Gradient-Free Methods for Saddle-Point Problems and Beyond» (30.08.2023). Candidate of Physical and Mathematical Sciences.

Rogozin Alexander Viktorovich, «Decentralized optimization over time-varying networks» (30.08.2023). Candidate of Physical and Mathematical Sciences.

Ostroukhov Petr Alekseevich, «High-order methods for optimization problems with specific structure» (28.12.2023). Candidate of Physical and Mathematical Sciences.

Публикации

2024

Metelev, D., Rogozin, A., Gasnikov, A., Kovalev, D. Decentralized saddle-point problems with different constants of strong convexity and strong concavity (2024) Computational Management Science, 21 (1), статья № 5. Scopus DOI Q2

Meruza Kubentayeva, Demyan Yarmoshik, Mikhail Persiianov, Alexey Kroshnin, Ekaterina Kotliarova, Nazarii Tupitsa, Dmitry Pasechnyuk, Alexander Gasnikov, Vladimir Shvetsov, Leonid Baryshev, Alexey Shurupov. Primal-Dual Gradient Methods for Searching Network Equilibria in Combined Models with Nested Choice Structure and Capacity Constraints (2024) Scopus DOI Q3

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

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

Nikita Kornilov, Ohad Shamir, Aleksandr Lobanov, Darina Dvinskikh, Alexander Gasnikov, Innokentiy Andreevich Shibaev, Eduard Gorbunov, Samuel Horváth. Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance (2024) Scopus DOI

2023

Gladin, E., Lavrik-Karmazin, M., Zainullina, K., Rudenko, V., Gasnikov, A., Takáč, M. Algorithm for Constrained Markov Decision Process with Linear Convergence (2023) Proceedings of Machine Learning Research, 206, pp. 11506-11533. Scopus DOI A*

Sadiev, A., Danilova, M., Gorbunov, E., Horváth, S., Gidel, G., Dvurechensky, P., Gasnikov, A., Richtárik, P. High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance (2023) Proceedings of Machine Learning Research, 202, pp. 29563-29648. Scopus DOI A*

Metelev, D., Rogozin, A., Kovalev, D., Gasnikov, A. Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks? (2023) Proceedings of Machine Learning Research, 202, pp. 24532-24554. Scopus DOI A*

Vasin, A., Gasnikov, A., Dvurechensky, P., Spokoiny, V. Accelerated gradient methods with absolute and relative noise in the gradient (2023) Optimization Methods and Software. Scopus DOI Q1

Pavel Dvurechensky, Petr Ostroukhov, Alexander Gasnikov, Cesar A Uribe. Near-optimal tensor methods for minimizing the gradient norm of convex functions and accelerated primal-dual tensor methods (2024) Scopus DOI Q1

Beznosikov, A.N., Gasnikov, A.V., Zainullina, K.E., Maslovskii, A.Y., Pasechnyuk, D.A. A Unified Analysis of Variational Inequality Methods: Variance Reduction, Sampling, Quantization, and Coordinate Descent (2023) Computational Mathematics and Mathematical Physics, 63 (2), pp. 147-174. Scopus DOI Q2

Gasnikova, E., Gasnikov, A., Kholodov, Y., Zukhba, A. An Evolutionary View on Equilibrium Models of Transport Flows (2023) Mathematics, 11 (4), статья № 858. Scopus DOI Q2

Turdakov, D.Y., Avetisyan, A.I., Arkhipenko, K.V., Antsiferova, A.V., Vatolin, D.S., Volkov, S.S., Gasnikov, A.V., Devyatkin, D.A., Drobyshevsky, M.D., Kovalenko, A.P., Krivonosov, M.I., Lukashevich, N.V., Malykh, V.A., Nikolenko, S.I., Oseledets, I.V., Perminov, A.I., Sochenkov, I.V., Tikhomirov, M.M., Fedotov, A.N., Khachay, M.Y. Trusted Artificial Intelligence: Challenges and Promising Solutions (2022) Doklady Mathematics, 106, pp. S9-S13. Scopus DOI Q2

Guminov, S., Gasnikov, A., Kuruzov, I. Accelerated methods for weakly-quasi-convex optimization problems (2023) Computational Management Science, 20 (1), статья № 36, . Scopus DOI Q2

Kornilov, N., Gasnikov, A., Dvurechensky, P., Dvinskikh, D. Gradient-free methods for non-smooth convex stochastic optimization with heavy-tailed noise on convex compact (2023) Computational Management Science, 20 (1), статья № 37, . Scopus DOI Q2

Lobanov, A., Veprikov, A., Konin, G., Beznosikov, A., Gasnikov, A., Kovalev, D. Non-smooth setting of stochastic decentralized convex optimization problem over time-varying Graphs (2023) Computational Management Science, 20 (1), статья № 48. Scopus DOI Q2

Alashqar, B.A., Gasnikov, A.V., Dvinskikh, D.M., Lobanov, A.V. Gradient-free Federated Learning Methods with l 1 and l 2-randomization for Non-smooth Convex Stochastic Optimization Problems (2023) Computational Mathematics and Mathematical Physics, 63 (9), pp. 1600-1653. Scopus DOI Q2

Alkousa, M.S., Gasnikov, A.V., Gladin, E.L., Kuruzov, I.A., Pasechnyuk, D.A., Stonyakin, F.S. Solving strongly convex-concave composite saddle-point problems with low dimension of one group of variables (2023) Sbornik Mathematics, 214 (3), pp. 285-333. Scopus DOI Q2

Chezhegov, S., Rogozin, A., Gasnikov, A. On Decentralized Nonsmooth Optimization (2023) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13930 LNCS, pp. 25-38. Scopus DOI Q3

Beznosikov, A., Gasnikov, A. SARAH-Based Variance-Reduced Algorithm for Stochastic Finite-Sum Cocoercive Variational Inequalities (2023) Springer Optimization and Its Applications, 202, pp. 47-57. Scopus DOI Q3

Demyan Yarmoshik, Alexander Rogozin, Alexander Gasnikov. Decentralized optimization with affine constraints over time-varying networks (2023) Scopus DOI Q3

Nikita Iltyakov, Mark Obozov, Igor Dyslevski, Demyan Yarmoshik, Meruza Kubentayeva, Alexander Gasnikov. On Accelerated Coordinate Descent Methods for Searching Equilibria in Two-Stage Transportation Equilibrium Traffic Flow Distribution Model (2023) Scopus DOI Q3

Tominin, Y.D., Tominin, V.D., Borodich, E.D., Kovalev, D.A., Dvurechensky, P.E., Gasnikov, A.V., Chukanov, S.V. On Accelerated Methods for Saddle-Point Problems with Composite Structure [Об ускоренных методах для седловых задач с композитной структурой] (2023) Computer Research and Modeling, 15 (2), pp. 433-467. Scopus DOI Q4

Lobanov, A., Anikin, A., Gasnikov, A., Gornov, A., Chukanov, S. Zero-Order Stochastic Conditional Gradient Sliding Method for Non-smooth Convex Optimization (2023) Communications in Computer and Information Science, 1881 CCIS, pp. 92-106. Scopus DOI Q4

Savchuk, O., Stonyakin, F., Alkousa, M., Zabirova, R., Titov, A., Gasnikov, A. Online Optimization Problems with Functional Constraints Under Relative Lipschitz Continuity and Relative Strong Convexity Conditions (2023) Communications in Computer and Information Science, 1881 CCIS, pp. 29-43. Scopus DOI Q4

Dvurechensky, P., Gasnikov, A., Tyurin, A., Zholobov, V. Unifying Framework for Accelerated Randomized Methods in Convex Optimization (2023) Springer Proceedings in Mathematics and Statistics, 425, pp. 511-561. Scopus DOI

Aleksandr Beznosikov, Martin Takáč, Alexander Gasnikov. Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities (2023) Scopus DOI

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

Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander V. Gasnikov. Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees (2023) Scopus DOI

Tkachenko S., Andreev A., Beznosikov A., Gasnikov A. Real Acceleration of Communication Process in Distributed Algorithms with Compression (2023), 14395 LNCS, pp. 99 - 109 Scopus DOI

2022

Kovalev, D., Beznosikov, A., Borodich, E., Gasnikov, A., Scutari, G. Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity (2022) Advances in Neural Information Processing Systems, 35. Scopus WOS DOI  A*

Kovalev, D., Gasnikov, A., Richtárik, P. Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling (2022) Advances in Neural Information Processing Systems, 35. Scopus WOS DOI A*

Tian, Y., Scutari, G., Cao, T., Gasnikov, A. Acceleration in Distributed Optimization under Similarity (2022) Proceedings of Machine Learning Research, 151, pp. 5721-5756. Scopus WOS DOI A*

Beznosikov, A., Richtárik, P., Diskin, M., Ryabinin, M., Gasnikov, A. Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees (2022) Advances in Neural Information Processing Systems, 35. Scopus WOS DOI A*

Beznosikov, A., Dvurechensky, P., Koloskova, A., Samokhin, V., Stich, S.U., Gasnikov, A. Decentralized Local Stochastic Extra-Gradient for Variational Inequalities (2022) Advances in Neural Information Processing Systems, 35. Scopus WOS DOI A*

Kovalev, D., Beznosikov, A., Sadiev, A., Persiianov, M., Richtárik, P., Gasnikov, A. Optimal Algorithms for Decentralized Stochastic Variational Inequalities (2022) Advances in Neural Information Processing Systems, 35. Scopus WOS DOI A*

Kovalev, D., Gasnikov, A. The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization (2022) Advances in Neural Information Processing Systems, 35. Scopus WOS DOI A*

Gorbunov, E., Danilova, M., Dobre, D., Dvurechensky, P., Gasnikov, A., Gidel, G. Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise (2022) Advances in Neural Information Processing Systems, 35. Scopus WOS DOI A*

Kovalev, D., Gasnikov, A. The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization (2022) Advances in Neural Information Processing Systems, 35. Scopus WOS DOI A*

Gasnikov, A., Novitskii, A., Novitskii, V., Abdukhakimov, F., Kamzolov, D., Beznosikov, A., Takáč, M., Dvurechensky, P., Gu, B. The Power of First-Order Smooth Optimization for Black-Box Non-Smooth Problems (2022) Proceedings of Machine Learning Research, 162, pp. 7241-7265. Scopus WOS DOI A*

Hanzely, S., Kamzolov, D., Pasechnyuk, D., Gasnikov, A., Richtárik, P., Takáč, M. A Damped Newton Method Achieves Global O(1/K2) and Local Quadratic Convergence Rate (2022) Advances in Neural Information Processing Systems, 35. Scopus WOS DOI A*

Tiapkin, D., Gasnikov, A. Primal-Dual Stochastic Mirror Descent for MDPs (2022) Proceedings of Machine Learning Research, 151, pp. 9723-9740. Scopus WOS DOI A*

Stonyakin F. , Gasnikov A. , Dvurechensky P. , Titov A. , Alkousa M. Generalized Mirror Prox Algorithm for Monotone Variational Inequalities: Universality and Inexact Oracle // Journal of Optimization Theory and Applications, Vol. 194, No. 3, P. 988 - 1013 Scopus WOS DOI Q1

Gorbunov E., Dvurechensky P., Gasnikov A. An accelerated method for derivative-free smooth stochastic convex optimization // SIAM Journal on Optimization, Vol. 32, No. 2, P. 1210 - 1238 Scopus WOS DOI Q1

Ivanova A., Dvurechensky P., Vorontsova E., Pasechnyuk D., Gasnikov A., Dvinskikh D., Tyurin A. Oracle Complexity Separation in Convex Optimization // Journal of Optimization Theory and Applications, Vol. 193, No. 1, P. 462 - 490 Scopus WOS DOI Q1

Anikin A., Gasnikov A., Gornov A., Kamzolov D., Maximov Y., Nesterov Y. Efficient numerical methods to solve sparse linear equations with application to PageRank // Optimization Methods and Software, Vol. 37, No. 3, P. 907 - 935 Scopus WOS DOI Q1

Gorbunov, E., Dvurechensky, P., Gasnikov, A. AN ACCELERATED METHOD FOR DERIVATIVE-FREE SMOOTH STOCHASTIC CONVEX OPTIMIZATION (2022) SIAM Journal on Optimization, 32 (2), pp. 1210-1238. Scopus WOS DOI Q1

Shibaev I., Dvurechensky P., Gasnikov A. Zeroth-order methods for noisy Hölder-gradient functions // Optimization Letters, Vol. 16, No. 7, P. 2123 - 2143 Scopus WOS DOI Q2

Tiapkin D., Gasnikov A., Dvurechensky P. Stochastic saddle-point optimization for the Wasserstein barycenter problem // Optimization Letters, Vol. 16, No. 7, P. 2145 - 2175 Scopus WOS DOI Q2

Sadiev A., Borodich E., Beznosikov A., Dvinskikh D., Chezhegov S., Tappenden R., Takáč M., Gasnikov A. Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes // EURO Journal on Computational Optimization, Vol. 10, P. 100041 Scopus WOS DOI Q2

Borodich E., Tominin V., Tominin Y., Kovalev D., Gasnikov A., Dvurechensky P. Accelerated variance-reduced methods for saddle-point problems // EURO Journal on Computational Optimization, Vol. 10, P. 100048 Scopus WOS DOI Q2

Gladin, E.L., Gasnikov, A.V., Ermakova, E.S. Vaidya’s Method for Convex Stochastic Optimization Problems in Small Dimension (2022) Mathematical Notes, 112 (1-2), pp. 183-190. Scopus WOS DOI Q2

Ablaev, S.S., Titov, A.A., Stonyakin, F.S., Alkousa, M.S., Gasnikov, A. Some Adaptive First-Order Methods for Variational Inequalities with Relatively Strongly Monotone Operators and Generalized Smoothness (2022) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13781 LNCS, pp. 135-150. Scopus WOS DOI Q2

Beznosikov, A., Gasnikov, A. Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities (2022) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13781 LNCS, pp. 151-162. Scopus WOS DOI Q2

Yarmoshik D., Rogozin A., Khamisov O.O., Dvurechensky P., Gasnikov A. Decentralized Convex Optimization Under Affine Constraints for Power Systems Control // Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13367, P. 62 - 75 Scopus WOS DOI Q3

Dvinskikh D., Tominin V., Tominin I., Gasnikov A. Noisy Zeroth-Order Optimization for Non-smooth Saddle Point Problems // Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13367, P. 18 - 33 Scopus WOS DOI Q3

Danilova M., Dvurechensky P., Gasnikov A., Gorbunov E., Guminov S., Kamzolov D., Shibaev I. Recent Theoretical Advances in Non-Convex Optimization // Springer Optimization and Its Applications, Vol. 191, P. 79 - 163 Scopus WOS DOI Q3

Chezhegov S., Novitskii A., Rogozin A., Parsegov S., Dvurechensky P., Gasnikov A. A General Framework for Distributed Partitioned Optimization // IFAC-PapersOnLine, Vol. 55, No. 13, P. 139 - 144 Scopus WOS DOI Q3

Dvinskikh D.M., Pirau V.V., Gasnikov A.V. On the relations of stochastic convex optimization problems with empirical risk minimization problems on p-norm balls // Computer Research and Modeling, Vol. 14, No. 2, P. 309 - 319 Scopus WOS DOI Q4

Alkousa M.S., Gasnikov A.V., Dvurechensky P.E., Sadiev A.A., Razouk L.Ya. An approach for the nonconvex uniformly concave structured saddle point problem // Computer Research and Modeling, Vol. 14, No. 2, P. 225 - 237 Scopus WOS DOI Q4

Pletnev N.V., Dvurechensky P.E., Gasnikov A.V. Application of gradient optimization methods to solve the Cauchy problem for the Helmholtz equation // Computer Research and Modeling, Vol. 14, No. 2, P. 417 - 444 Scopus WOS DOI Q4

Rogozin, A., Yarmoshik, D., Kopylova, K., Gasnikov, A. Decentralized Strongly-Convex Optimization with Affine Constraints: Primal and Dual Approaches (2022) Communications in Computer and Information Science, 1739 CCIS, pp. 93-105. Scopus WOS DOI Q4

Maslovskiy, A., Kunitsyn, A., Gasnikov, A. Application of Attention Technique for Digital Pre-distortion (2022) Communications in Computer and Information Science, 1739 CCIS, pp. 168-182. Scopus WOS DOI Q4

Pletnev, N.V., Dvurechensky, P.E., Gasnikov, A.V. Application of gradient optimization methods to solve the Cauchy problem for the Helmholtz equation [Применение градиентных методов оптимизации для решения задачи Коши для уравнения Гельмгольца] (2022) Computer Research and Modeling, 14 (2), pp. 417-444. Scopus WOS DOI Q4

2021

Kovalev, D., Gasanov, E., Gasnikov, A., Richtárik, P. Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks (2021) Advances in Neural Information Processing Systems, 27, pp. 22325-22335. Scopus WOS DOI A*

Kovalev, D., Shulgin, E., Richtárik, P., Rogozin, A., Gasnikov, A. ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks (2021) Proceedings of Machine Learning Research, 139, pp. 5784-5793. Scopus WOS DOI A*

Daneshmand, A., Scutari, G., Dvurechensky, P., Gasnikov, A. Newton Method over Networks is Fast up to the Statistical Precision (2021) Proceedings of Machine Learning Research, 139, pp. 2398-2409. Scopus WOS DOI A*

Dvurechensky, P., Gorbunov, E., Gasnikov, A. An accelerated directional derivative method for smooth stochastic convex optimization (2021) European Journal of Operational Research, 290 (2), pp. 601-621. Scopus DOI Q1

Stonyakin, F., Tyurin, A., Gasnikov, A., Dvurechensky, P., Agafonov, A., Dvinskikh, D., Alkousa, M., Pasechnyuk, D., Artamonov, S., Piskunova, V. Inexact model: a framework for optimization and variational inequalities (2021) Optimization Methods and Software, 36 (6), pp. 1155-1201. Scopus DOI Q1

Uribe, C.A., Lee, S., Gasnikov, A., Nedić, A. A dual approach for optimal algorithms in distributed optimization over networks (2021) Optimization Methods and Software, 36 (1), pp. 171-210. Scopus WOS DOI Q1

Nesterov, Y., Gasnikov, A., Guminov, S., Dvurechensky, P. Primal–dual accelerated gradient methods with small-dimensional relaxation oracle (2021) Optimization Methods and Software, 36 (4), pp. 773-810. Scopus WOS DOI Q1

Ivanova, A., Dvurechensky, P., Gasnikov, A., Kamzolov, D. Composite optimization for the resource allocation problem (2021) Optimization Methods and Software, 36 (4), pp. 720-754. Scopus DOI Q1

Kamzolov, D., Dvurechensky, P., Gasnikov, A.V. Universal intermediate gradient method for convex problems with inexact oracle (2021) Optimization Methods and Software, 36 (6), pp. 1289-1316. Scopus DOI Q1

Dvurechensky P., Kamzolov D., Lukashevich A., Lee S., Ordentlich E., Uribe C.A., Gasnikov A. Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization // EURO Journal on Computational Optimization, Vol. 10, P. 100045 Scopus WOS DOI Q2

Novitskii V., Gasnikov A. Improved exploitation of higher order smoothness in derivative-free optimization // Optimization Letters, Vol. 16, No. 7, P. 2059 - 2071 Scopus WOS DOI Q2

Kubentayeva, M., Gasnikov, A. Finding equilibria in the traffic assignment problem with primal-dual gradient methods for stable dynamics model and beckmann model (2021) Mathematics, 9 (11), статья № 1217. Scopus WOS DOI Q2

Vorontsova, E.A., Gasnikov, A.V., Dvurechensky, P.E., Ivanova, A.S., Pasechnyuk, D.A. Numerical Methods for the Resource Allocation Problem in a Computer Network (2021) Computational Mathematics and Mathematical Physics, 61 (2), pp. 297-328. Scopus DOI Q2

Gasnikov, A.V., Dvinskikh, D.M., Dvurechensky, P.E., Kamzolov, D.I., Matyukhin, V.V., Pasechnyuk, D.A., Tupitsa, N.K., Chernov, A.V. Accelerated Meta-Algorithm for Convex Optimization Problems (2021) Computational Mathematics and Mathematical Physics, 61 (1), pp. 17-28. Scopus DOI Q2

Gorbunov E., Rogozin A., Beznosikov A., Dvinskikh D., Gasnikov A. Recent Theoretical Advances in Decentralized Distributed Convex Optimization // Springer Optimization and Its Applications, Vol. 191, P. 253 - 325 Scopus WOS DOI Q3

Gladin, E., Alkousa, M., Gasnikov, A. Solving Convex Min-Min Problems with Smoothness and Strong Convexity in One Group of Variables and Low Dimension in the Other // Automation and Remote Control, 82 (10), pp. 1679-1691. Scopus DOI Q3

Tupitsa, N., Dvurechensky, P., Gasnikov, A., Guminov, S. Alternating minimization methods for strongly convex optimization (2021) Journal of Inverse and Ill-Posed Problems, 29 (5), pp. 721-739. Scopus WOS DOI Q3

Dvinskikh, D., Gasnikov, A. Decentralized and parallel primal and dual accelerated methods for stochastic convex programming problems (2021) Journal of Inverse and Ill-Posed Problems, 29 (3), pp. 385-405. Scopus WOS DOI Q3

Rogozin, A., Lukoshkin, V., Gasnikov, A., Kovalev, D., Shulgin, E. Towards Accelerated Rates for Distributed Optimization over Time-Varying Networks (2021) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13078 LNCS, pp. 258-272. Scopus WOS DOI Q3

Matyukhin, V., Kabanikhin, S., Shishlenin, M., Novikov, N., Vasin, A., Gasnikov, A. Convex Optimization with Inexact Gradients in Hilbert Space and Applications to Elliptic Inverse Problems (2021) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12755 LNCS, pp. 159-175. Scopus WOS DOI Q3

Safin, K., Dvurechensky, P., Gasnikov, A. Adaptive Gradient-Free Method for Stochastic Optimization (2021) Communications in Computer and Information Science, 1514 CCIS, pp. 95-108. Scopus DOI Q4

Pasechnyuk, D., Dvurechensky, P., Omelchenko, S., Gasnikov, A. Stochastic Optimization for Dynamic Pricing (2021) Communications in Computer and Information Science, 1514 CCIS, pp. 82-94. Scopus WOS DOI Q4

Ivanova, A., Pasechnyuk, D., Grishchenko, D., Shulgin, E., Gasnikov, A., Matyukhin, V. Adaptive Catalyst for Smooth Convex Optimization (2021) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13078 LNCS, pp. 20-37. Scopus DOI Q4

Beznosikov, A., Rogozin, A., Kovalev, D., Gasnikov, A. Near-Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks (2021) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13078 LNCS, pp. 246-257. Scopus WOS DOI Q4

Sadiev, A., Beznosikov, A., Dvurechensky, P., Gasnikov, A. Zeroth-Order Algorithms for Smooth Saddle-Point Problems (2021) Communications in Computer and Information Science, 1476 CCIS, pp. 71-85. Scopus DOI Q4

Maslovskiy, A., Pasechnyuk, D., Gasnikov, A., Anikin, A., Rogozin, A., Gornov, A., Antonov, L., Vlasov, R., Nikolaeva, A., Begicheva, M. Non-convex Optimization in Digital Pre-distortion of the Signal (2021) Communications in Computer and Information Science, 1476 CCIS, pp. 54-70. Scopus WOS DOI Q4

Gladin, E., Sadiev, A., Gasnikov, A., Dvurechensky, P., Beznosikov, A., Alkousa, M. Solving Smooth Min-Min and Min-Max Problems by Mixed Oracle Algorithms (2021) Communications in Computer and Information Science, 1476 CCIS, pp. 19-40. Scopus DOI Q4

Titov, A.A., Stonyakin, F.S., Alkousa, M.S., Gasnikov, A.V. Algorithms for Solving Variational Inequalities and Saddle Point Problems with Some Generalizations of Lipschitz Property for Operators (2021) Communications in Computer and Information Science, 1476 CCIS, pp. 86-101. Scopus DOI Q4

Beznosikov, A., Novitskii, V., Gasnikov, A. One-Point Gradient-Free Methods for Smooth and Non-smooth Saddle-Point Problems (2021) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12755 LNCS, pp. 144-158. Scopus DOI Q4

Kotliarova, E.V., Gasnikov, A.V., Gasnikova, E.V., Yarmoshik, D.V. Finding equilibrium in two-stage traffic assignment model [Поиск равновесий в двухстадийных моделях распределения транспортных потоков по сети] (2021) Computer Research and Modeling, 13 (2), pp. 365-379. Scopus WOS DOI Q4

Beznosikov, A., Rogozin, A., Scutari, G., Gasnikov, A. Distributed Saddle-Point Problems Under Similarity (2021) Advances in Neural Information Processing Systems, 10, pp. 8172-8184. Scopus WOS DOI

Rogozin, A., Bochko, M., Dvurechensky, P., Gasnikov, A., Lukoshkin, V. An Accelerated Method for Decentralized Distributed Stochastic Optimization over Time-Varying Graphs (2021) Proceedings of the IEEE Conference on Decision and Control, 2021-December, pp. 3367-3373. Scopus WOS DOI

Agafonov, A., Dvurechensky, P., Scutari, G., Gasnikov, A., Kamzolov, D., Lukashevich, A., Daneshmand, A. An Accelerated Second-Order Method for Distributed Stochastic Optimization (2021) Proceedings of the IEEE Conference on Decision and Control, 2021-December, pp. 2407-2413. Scopus WOS DOI

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

2020

Gorbunov, E., Danilova, M., Gasnikov, A. Stochastic optimization with heavy-tailed noise via accelerated gradient clipping (2020) Advances in Neural Information Processing Systems, 2020-December. Scopus WOS DOI A*

Rogozin, A., Uribe, C.A., Gasnikov, A.V., Malkovsky, N., Nedic, A. Optimal distributed convex optimization on slowly time-varying graphs (2020) IEEE Transactions on Control of Network Systems, 7 (2), статья № 8882272, pp. 829-841. Scopus WOS DOI Q1

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