
Gasnikov Alexander Vladimirovich
Doctor of Physical and Mathematical Sciences, Professor, Corresponding Member of the Russian Academy of Sciences.
Head of the Laboratory of Mathematical Methods of Optimization, Head of the Department of Mathematical Foundations of Control
Ссылка на страницу Google Scholar
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 May 2025 — Corresponding Member of the Department of Mathematical Sciences of the Russian Academy of Sciences
since August 2024 — Member of the Council for Science and Education under the President of Russia
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
The “Scientific Breakthrough 2026” Award in the “Digitalization in Science”, established by the Academy of Sciences of the Republic of Tatarstan. The award was presented in Kazan on 11 February 2026.
Recipient of the National Expert 2025 Award presented by National Priorities, an autonomous non-profit organization, for contributions to expert activities, analytical reports and the promotion of national projects. The award was presented on 4 February 2026
Included in the Top 2% Scientists ranking in Artificial Intelligence
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.
Novitsky Vasily, "New Bounds for One-point Stochastic Gradient-free Methods" (7.11.2024). Candidate of Physical and Mathematical Sciences.
Yarmoshik Demyan Valerevich, "Decentralized optimization with affine constraints" (23.12.2024). Candidate of Physical and Mathematical Sciences.
Maslovsky Alexander Yuryevich, "Optimization of digital pre-distortion Wiener-Hammerstein like functionals for cancellation of Inter modulation distortions" (26.12.2024). Candidate of Technical Sciences.
Shibaev Innokenty Andreevich, "Безградиентные методы оптимизации для функций с гельдеровым градиентом" (26.12.2024). Candidate of Physical and Mathematical Sciences.
Beznosikov Alexander Nikolaevich, "On advanced topics in complexity theory of numerical optimization methods: distributivity, stochasticity and generalization to broader classes of problems" (06.11.2025). Doctor of Physico-mathematical Sciences.
Kuruzov Ilya Alekseevich, "First-Order Methods for Optimization Problems with Inexact Gradient Information" (11.12.2025). Candidate of Physico-mathematical Sciences.
Lobanov, Alexander Vladimirovich, "Gradient-Free Methods for Convex Optimization under Noise Conditions" (24.12.2025). Candidate of Physico-mathematical Sciences.
Artem Dmitrievich Agafonov, "Inexact High-order methods" (24.12.2025). Candidate of Physico-mathematical Sciences.
Nikita V. Pletnev, "Применение градиентных методов оптимизации для решения некоторых обратных задач математической физики" (24.12.2025). Candidate of Physico-mathematical Sciences.
Публикации
Maxim Divilkovskiy, Alexander Gasnikov. Stochastic Decentralized Optimization of Non-Smooth Convex and Convex-Concave Problems over Time-Varying Networks The 40th Annual AAAI Conference on Artificial Intelligence A*
Aleksandr Beznosikov, Georgiy Kormakov, Alexander Grigorievskiy, Mikhail Rudakov, Ruslan Nazykov, Alexander Rogozin, Anton Vakhrushev, Andrey Savchenko, Martin Takáč, Alexander Gasnikov. Exploring New Frontiers in Vertical Federated Learning: the Role of Saddle Point Reformulation (2026) Journal of Optimization Theory and Applications DOI Q1
Sergey Stanko, Timur Karimullin, Aleksandr Beznosikov, Alexander Gasnikov. Accelerated Methods with Compression for Horizontal and Vertical Federated Learning: S. Stanko et al. (2026) Journal of Optimization Theory and Applications Q1
Artem Agafonov, Anton Novitskii, Alexander Rogozin, Yury Sokolov, Dmitry Kamzolov, Alexander Dyakonov, Martin Takáč, Alexander Gasnikov. Decentralized Inexact Cubic Newton Method with Consensus Procedure (2026). IEEE Access, 14, 83513–83540. DOI: 10.1109/ACCESS.2026.3695635. Q1
Nail Bashirov, Alexander Gasnikov, Aleksandr Lobanov. Zeroth-order methods for non-smooth stochastic problems under heavy-tailed noise (2026) Optimization Methods and Software Q2
Denis Belomestny, Alexander Gasnikov, Egor Gladin, Alexey Naumov, Artemy Rubtsov, Yuri Sapronov, Daniil Tiapkin, Nikita Yudin. Mathematical methods of reinforcement learning (2026). Успехи математических наук, 81:4(490), 3–90. DOI: 10.4213/rm10328. Q2
Anastasiia Murzina, Ilya Kuruzov, Alexander Gasnikov. Decentralized Gradient Descent with an Increasing Consensus Procedure Accuracy (2026). MOTOR 2026. Lecture Notes in Computer Science, 16687, 32–47. DOI: 10.1007/978-3-032-31390-4_3. Q2
Anton Novitskii, Alexander Rogozin, Alexander Gasnikov. Decentralized Gradient Descent with an Increasing Consensus Procedure Accuracy (2026). MOTOR 2026. Lecture Notes in Computer Science, 16687, 48–63. DOI: 10.1007/978-3-032-31390-4_4. Q2
Artem Vasin, Alexander Gasnikov. Lower and upper bounds of the convergence rate of gradient methods with composite noise in gradient (2026) arXiv preprint arXiv:2603.12376
Ali Jnadi, Hadi Salloum, Yaroslav Kholodov, Alexander Gasnikov, Karam Almaghout. SCOPE: Smooth Convex Optimization for Planned Evolution of Deformable Linear Objects (2026) arXiv preprint arXiv:2601.19742
Hadi Salloum, Ali Jnadi, Yaroslav Kholodov, Alexander Gasnikov. Quantum-Inspired Episode Selection for Monte Carlo Reinforcement Learning via QUBO Optimization (2026) arXiv preprint arXiv:2601.17570
Boris Prokhorov, Semyon Chebykin, Alexander Gasnikov, Aleksandr Beznosikov. Gradient-Free Approaches is a Key to an Efficient Interaction with Markovian Stochasticity (2026) arXiv preprint arXiv:2601.01160
Alyona Nekrasova, Makar Sidorov, Savelii Chezhegov, Alexander Gasnikov, Margarita Preobrazhenskaia, Igor Preobrazhensky, Eduard Gorbunov. Weak-L^α Noise, Strong Guarantees: Gradient Clipping under Affine Heavy Tails (2026). arXiv preprint arXiv:2610.28107.
Darina M. Dvinskikh, Anton G. Novitskii, Ewsey R. Obzherin, Alexander V. Gasnikov. TIGER: Tunable-Geometry Accelerated Gradient Sliding with Adaptive Safeguards under Similarity (2026). arXiv preprint arXiv:2610.25504.
Artem Vasin, Alexander Tyurin, Alexander Gasnikov. Adaptive First-Order Methods with Composite Gradient Error (2026). arXiv preprint arXiv:2610.24863.
Mikhail Rudomanov, Ivan Fomin, Alexander V. Gasnikov, Fedor S. Stonyakin. Descending Everest with First-Order Oracles: Oracle Complexity of Convex Optimization under (L_0,L_1)-Smoothness (2026). arXiv preprint arXiv:2610.21461.
Yuriy Dorn, Dmitrii Vishovan, Kirill Novoselov, Ilya Kuruzov, Darina Dvinskikh, Alexander Gasnikov. Beyond Aggregate Drift: Optimal Client-Specific Windows in Federated Learning (2026). arXiv preprint arXiv:2610.15543.
Yuriy Dorn, Osman Osmanov, Timofei Loginov, Nazarii Tupitsa, Darina Dvinskikh, Alexander Gasnikov. Adaptive two-points zero-order accelerated methods for stochastic convex optimization problems (2026). arXiv preprint arXiv:2610.15202.
Nhat Trung Nguyen, Ivan Dorofeev, Irina Podlipnova, Yuriy Dorn, Alexander Gasnikov. Complexity of Multiblock Convex-Concave Saddle-Point Problems with General Smooth Coupling (2026). arXiv preprint arXiv:2610.12656.
Kirill Novoselov, Yuriy Dorn, Darina Dvinskikh, Alexander Gasnikov. Optimal Rates for Federated Variational Inequalities under different relaxations of bounded variance assumption (2026). arXiv preprint arXiv:2610.12641.
Artem Agafonov, Aslan Ashabokov, Dmitry Kamzolov, Alexander D'yakonov, Alexander Gasnikov, Martin Takáč. Matching the Lower Bounds: Stochastic Contracting Cubic Newton and Its Optimal Acceleration (2026). arXiv preprint arXiv:2610.11693.
Timofei Loginov, Darina Dvinskikh, Nazarii Tupitsa, Osman Osmanov, Yuriy Dorn, Alexander Gasnikov. Minimax Oracle Call Complexity, Rounds and Admissible Noise in Zeroth-Order Optimization of Highly Smooth Functions (2026). arXiv preprint arXiv:2610.05517.
Ilya Kuruzov, Dmitrii Vishovan, Kirill Novoselov, Yuriy Dorn, Darina Dvinskikh, Alexander Gasnikov. Asking the Crowd the Right Question: Bias-Cancelling Weights for Federated Learning (2026). arXiv preprint arXiv:2610.04671.
Yuriy Dorn, Darina Dvinskikh, Timofei Loginov, Osman Osmanov, Aleksandr Shestakov, Nazarii Tupitsa, Alexander Gasnikov. Lower Bounds For Gradient-Free Convex Optimization And Convex-Concave Saddle-Point Problems (2026). arXiv preprint arXiv:2610.00345.
Anton Anikin, Alexander Gornov, Tatiana Zarodnyuk, Alexander Gasnikov. Greedy sign-based box splitting: exact solvable classes, sharp thresholds and order-oracle complexity (2026). arXiv preprint arXiv:2609.37444.
Darina Dvinskikh, Anton Novitskii, Demyan Yarmoshik, Alexander Rogozin, Vladislav Matyukhin, Alexander Gasnikov. Accelerated Consensus and Decentralized Optimization over Slowly Varying Networks (2026). arXiv preprint arXiv:2609.33824.
Aleksandr Lobanov, Darina Dvinskikh, Alexander Gasnikov. Accelerated Stochastic Method under (H_0,H_1)-Smoothness and Heavy-Tailed Noise (2026). arXiv preprint arXiv:2609.33415.
Ewsey Obzherin, Ilya Khomchenko, Natalia Shelegeda, Nhat Trung Nguyen, Demyan Yarmoshik, Alexander Rogozin, Alexander Gasnikov. Decentralized Optimization with Cross-Coupled Mixed Affine Constraints (2026). arXiv preprint arXiv:2609.33021.
Artem Agafonov, Aslan Ashabokov, Alexander D'yakonov, Martin Takáč, Alexander Gasnikov, Dmitry Kamzolov. Optimal Parameter-Free Second-order Acceleration with Inexact Hessians under Generalized Smoothness (2026). arXiv preprint arXiv:2609.32977.
Alexandra Suvorikova, Egor Gladin, Darina Dvinskikh, Artem Agafonov, Mohammad Alkousa, Yuriy Dorn, Vladislav Matyukhin, Alexander Gasnikov. Clipped or Unclipped? Finite-Sample Trade-offs for Averaged SGD under Heavy-Tailed Noise (2026). arXiv preprint arXiv:2609.32962.
Timofei Loginov, Alexander Gasnikov, Yuriy Dorn, Aleksandr Shestakov, Nazarii Tupitsa, Osman Osmanov, Darina Dvinskikh. The Complexity of Convex Optimization with Mismatched Geometry (2026). arXiv preprint arXiv:2609.32910.
Irina Podlipnova, Maxim Mashtaler, Artem Agafonov, Yuriy Dorn, Alexander Gasnikov. Smooth or Separable? Sparse Block Acceleration for Entropy-Regularized Linear Programs (2026). arXiv preprint arXiv:2609.32558.
Ivan Fomin, Alexander V. Gasnikov. Saddle-Point Problems with a Low-Dimensional Block Do Not Need Accurate Inner Solves (2026). arXiv preprint arXiv:2609.32441.
Ewsey R. Obzherin, Roman M. Mozhaev, Alexander V. Gasnikov, Martin Takáč, Artem A. Agafonov, Dmitry I. Kamzolov. Certified Residual Quasi-Newton Methods for Distributed Variational Inequalities (2026). arXiv preprint arXiv:2609.22481.
Yury A. Sokolov, Maxim K. Mashtaler, Alexander V. Gasnikov, Martin Takáč, Dmitry I. Kamzolov, Artem D. Agafonov. Application of Optimal Inexact Second-Order Acceleration to Distributed Stochastic Optimization under Statistical Similarity (2026). arXiv preprint arXiv:2609.21878.
Darina Dvinskikh, Alexander Gasnikov, Aleksandr Lobanov, Ilgam Latypov. Localize, Restart, Accelerate: Stochastic Optimization under Generalized Smoothness (2026). arXiv preprint arXiv:2609.06555.
Nhat Trung Nguyen, Alexander Gasnikov. Sliding Methods for Hölder-Smooth Convex--Concave Minimax Optimization with Bilinear Coupling (2026). arXiv preprint arXiv:2608.03846.
Alexandra Suvorikova, Igor Pavlov, Artem Vasin, Georgii Bychkov, Anastasia Antsiferova, Darina Dvinskikh, Alexander Gasnikov. Wall-Clock Complexity for Zeroth-Order Optimization with Tunable Oracle Fidelity (2026). arXiv preprint arXiv:2605.31346.
Arutyun Avetisyan, Darina Dvinskikh, Alexander Gasnikov, Vladimir Temlyakov, Nazarii Tupitsa, Denis Turdakov. Stochastic Optimization and Data Science (2026). arXiv preprint arXiv:2605.16875.
Stepan Kulibaba, Kirill Labzin, Artem Dzhalilov, Roman Pakhomov, Oleg Svidchenko, Alexander Gasnikov, Aleksei Shpilman. SDG-MoE: Signed Debate Graph Mixture-of-Experts (2026). arXiv preprint arXiv:2605.08322.
Valery Krivchenko, Alexander Gasnikov, Dmitry Kovalev. Stronger constraints for smooth min-max games (2026). arXiv preprint arXiv:2603.17053.
Vadim Abronin, Alexander Gasnikov, Darina Dvinskikh. Gradient-Free Methods for Stochastic Convex Optimization with Stochastic Functional Constraints (2026). arXiv preprint arXiv:2609.35946.
2025
Demyan Yarmoshik, Alexander Rogozin, Nikita Kiselev, Daniil Dorin, Alexander Gasnikov, Dmitry Kovalev. Decentralized Optimization with Coupled Constraints (2025) The International Conference on Learning Representations (ICLR) A*
Savelii Chezhegov, Klyukin Yaroslav, Andrei Semenov, Aleksandr Beznosikov, Alexander Gasnikov, Samuel Horváth, Martin Takáč, Eduard Gorbunov (2025) Proceedings of the 42nd International Conference on Machine Learning (ICML) A*
Ekaterina Borodich, Alexander Gasnikov, Dmitry Kovalev. On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms (2025) Forty-second International Conference on Machine Learning (ICML) A*
Xiaokai Chen, Ilya Kuruzov, Gesualdo Scutari, Alexander Gasnikov. A parameter-free decentralized algorithm for composite convex optimization (2025) 2025 IEEE 64th Conference on Decision and Control (CDC) A
Roman Krawtschenko, César A Uribe, Alexander Gasnikov, Pavel Dvurechensky. Distributed optimization with quantization for computing wasserstein barycenters (2025) 2025 IEEE 64th Conference on Decision and Control (CDC) A
Dmitry Kovalev, Alexander Gasnikov, Grigory Malinovsky. An optimal algorithm for strongly convex min-min optimization (2025) The 41st Conference on Uncertainty in Artificial Intelligence A
Dmitrii Pasechniuk, Pavel Dvurechensky, César A Uribe, Alexander Gasnikov. Decentralised convex optimisation with probability-proportional-to-size quantization (2025) Q1
Nikita Kornilov, Mohammad Alkousa, Eduard Gorbunov, Fedor Stonyakin, Pavel Dvurechensky, Alexander Gasnikov. Intermediate gradient methods with relative inexactness (2025) Journal of Optimization Theory and Applications Q1
Aleksandr Vladimirovich Lobanov, Alexander Vladimirovich Gasnikov. Survey of modern smooth optimization algorithms with comparison oracle (2025) Doklady Mathematics Q2
Alexander Gasnikov, Angelia Nedich. Preface for the special issue advances in distributed optimization (2025) Optimization Methods and Software Q2
Artem Agafonov, Dmitry Kamzolov, Rachael Tappenden, Alexander Gasnikov, Martin Takáč. Flecs: A federated learning second-order framework via compression and sketching (2025) Optimization Methods and Software Q2
Aleksandr Beznosikov, Ivan Stepanov, Artyom Voronov, Alexander Gasnikov. One-point feedback for composite optimization with applications to distributed and federated learning (2025) Optimization Methods and Software Q2
Oleg S Savchuk, Fedor Sergeevich Stonyakin, Aleksandr A Vyguzov, Mohammad Soud Alkousa, Alexander Vladimirovich Gasnikov. Adaptive Primal–Dual Methods with an Inexact Oracle for Relatively Smooth Optimization Problems and Their Applications to Recovering Low-Rank Matrices (2025) Computational Mathematics and Mathematical Physics Q2
Александр Владимирович Лобанов, Александр Владимирович Гасников. Обзор современных алгоритмов гладкой оптимизации со сравнительным оракулом (2025) Доклады Российской академии наук. Математика, информатика, процессы управления Q2
Олег Сергеевич Савчук, Фёдор Сергеевич Стонякин, Александр Альбертович Выгузов, Мохаммад Соуд Алкуса, Александр Владимирович Гасников. Адаптивные прямо-двойственные методы с неточным оракулом для относительно гладких оптимизационных задач и их приложения к задачам восстановления малоранговых матриц (2025) Журнал вычислительной математики и математической физики Q2
Александр Владимирович Гасников, Владимир Николаевич Темляков. Некоторые оценки снизу для оптимального восстановления функций со смешанной гладкостью по выборке (2025) Математический сборник Q2
SS ABLAEV, FS STONYaKIN, MN FEDOTOV, MS ALKUSA, OS SAVChUK, AV GASNIKOV. ISSLEDOVANIE GRADIENTNOGO METODA S NETOChNOY INFORMATsIEY O GRADIENTE NA NEKOTORYKh KLASSAKh (L0, L1)-GLADKIKh NEVYPUKLYKh ZADACh (2025) Avtomatika i telemehanika Q3
Seydamet Serverovich Ablaev, Fedor Sergeevich Stonyakin, Maksim Nikolaevich Fedotov, Mohammad Soud Alkousa, Oleg S Savchuk, Alexander Vladimirovich Gasnikov. Study of gradient method with inexact gradient information on some classes of (L0;L1)-smooth non-convex problems (2025) Avtomatika i Telemekhanika Q3
Сейдамет Серверович Аблаев, Фёдор Сергеевич Стонякин, Максим Николаевич Федотов, Мохаммад Соуд Алкуса, Олег Сергеевич Савчук, Александр Владимирович Гасников. Исследование градиентного метода с неточной информацией о градиенте на некоторых классах (L0;L1)-гладких невыпуклых задач (2025) Автоматика и телемеханика Q3
SS Ablaev, FS Stonyakin, MN Fedotov, MS Alkousa, OS Savchuk, AV Gasnikov. A Gradient Method with Inexact Gradient Information: A Study on Some Classes of (L0, L1)-Smooth Nonconvex Problems (2025) Automation and Remote Control Q3
Artem Vasin, Valery Krivchenko, Dmitry Kovalev, Fedyor Stonyakin, Nazari Tupitsa, Pavel Dvurechensky, Mohammad Alkousa, Nikita Kornilov, Alexander Gasnikov. On Solving Minimization and Min-Max Problems by First-Order Methods with Relative Error in Gradients (2025)
Hadi Salloum, Roland Hildebrand, Nhat Trung Nguyen, Vitali Pirau, Amer Al Badr, Mohammad Alkousa, Alexander Gasnikov. Speeding up the Goemans-Williamson randomized procedure by difference-of-convex optimization (2026) arXiv preprint arXiv:2512.08852
Aleksandr Shestakov, Nail Bashirov, Andrei Semenov, Alexander Gasnikov, Martin Takáč, Aleksandr Beznosikov, Dmitry Kamzolov. Adaptive Regularized Newton Method with Inexact Hessian (2026) arXiv preprint arXiv:2512.08775
Mark Obozov, Michael Diskin, Aleksandr Beznosikov, Alexander Gasnikov, Serguei Barannikov. Synthetic Proofs with Tool-Integrated Reasoning: Contrastive Alignment for LLM Mathematics with Lean (2025) Proceedings of The 3rd Workshop on Mathematical Natural Language Processing (MathNLP 2025)
Ilgam Latypov, Alexandra Suvorikova, Alexey Kroshnin, Alexander Gasnikov, Yuriy Dorn. UCB-type Algorithm for Budget-Constrained Expert Learning (2025) arXiv preprint arXiv:2510.22654
Laith Nayal, Hadi Salloum, Ahmad Taha, Yaroslav Kholodov, Alexander Gasnikov. Training-Free Out-Of-Distribution Segmentation With Foundation Models (2025) arXiv preprint arXiv:2510.02909
Artem Agafonov, Vladislav Ryspayev, Samuel Horváth, Alexander Gasnikov, Martin Takáč, Slavomir Hanzely. Simple Stepsize for Quasi-Newton Methods with Global Convergence Guarantees (2025) arXiv preprint arXiv:2508.19712
Valentin Leplat, Sergio Mayorga, Roland Hildebrand, Alexander Gasnikov. Norm-Constrained Flows and Sign-Based Optimization: Theory and Algorithms (2025) arXiv preprint arXiv:2508.18510
Nikolay Kutuzov, Makar Baderko, Stepan Kulibaba, Artem Dzhalilov, Daniel Bobrov, Maxim Mashtaler, Alexander Gasnikov. AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models (2025) arXiv preprint arXiv:2508.18182
Stepan Kulibaba, Artem Dzhalilov, Roman Pakhomov, Oleg Svidchenko, Alexander Gasnikov, Aleksei Shpilman. Kompeteai: Accelerated autonomous multi-agent system for end-to-end pipeline generation for machine learning problems (2025) arXiv preprint arXiv:2508.10177
Ilya Kuruzov, Xiaokai Chen, Gesualdo Scutari, Alexander Gasnikov. Adaptive stepsize selection in decentralized convex optimization (2025) arXiv preprint arXiv:2507.23725
Nikita Kornilov, Philip Zmushko, Andrei Semenov, Mark Ikonnikov, Alexander Gasnikov, Alexander Beznosikov. Sign Operator for Coping with Heavy-Tailed Noise in Non-Convex Optimization: High Probability Bounds Under (L0;L1)-Smoothness (2025) arXiv preprint arXiv:2502.07923
Aleksandr Lobanov, Alexander Gasnikov. Power of generalized smoothness in stochastic convex optimization: First-and zero-order algorithms (2025) arXiv preprint
Hadi Salloum, Ali Jnadi, Ahmad Hamdan, Yaroslav Kholodov, Alexander Gasnikov. Tensor-Driven Optimization for Formula 1 Resource-Constrained Scheduling (2025) International Conference on Computational Optimization (ICOMP)
Hadi Salloum, Kirill Novoselov, Aleksandr Pochtarev, Alexander Gasnikov. Higher-Order vs. Quadratic Binary Optimization: is Better for Probability Optimization with Tensor Sampling? (2025) International Conference on Computational Optimization (ICOMP)
2024
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 A*
Ilya Kuruzov, Gesualdo Scutari, Alexander Gasnikov. Achieving linear convergence with parameter-free algorithms in decentralized optimization (2024) Advances in Neural Information Processing Systems A*
Artem Agafonov, Petr Ostroukhov, Roman Mozhaev, Konstantin Yakovlev, Eduard Gorbunov, Martin Takác, Alexander Gasnikov, Dmitry Kamzolov. Exploring jacobian inexactness in second-order methods for variational inequalities: lower bounds, optimal algorithms and quasi-newton approximations (2024) Advances in Neural Information Processing Systems A*
Nikita Kornilov, Petr Mokrov, Alexander Gasnikov, Aleksandr Korotin. Optimal flow matching: Learning straight trajectories in just one step (2024) Advances in Neural Information Processing Systems A*
Dmitry Kamzolov, Dmitry Pasechnyuk, Artem Agafonov, Alexander Gasnikov, Martin Takáč. Optami: Global superlinear convergence of high-order methods (2024) A*
Dmitry Kovalev, Ekaterina Borodich, Alexander Gasnikov, Dmitrii Feoktistov. Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks (2024) A*
Aleksandr Lobanov, Alexander Gasnikov, Andrei Krasnov. Acceleration exists! optimization problems when oracle can only compare objective function values (2024) A*
Puchkin, N., Gorbunov, E., Kutuzov, N., Gasnikov, A. Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems (2024) Proceedings of Machine Learning Research, 238, pp. 856-864. Scopus A
Nazykov, R., Shestakov, A., Solodkin, V., Beznosikov, A., Gidel, G., Gasnikov, A. Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases (2024) Proceedings of Machine Learning Research, 238, pp. 4870-4878. Scopus A