Публикации

Gasnikov, A.V., Alkousa, M.S., Lobanov, A.V., Dorn, Y.V., Stonyakin, F.S., Kuruzov, I.A., Singh, S.R. On Quasi-Convex Smooth Optimization Problems by a Comparison Oracle (2024) Russian Journal of Nonlinear Dynamics, 20 (5), pp. 813-825. Scopus DOI  Q3

Hildebrand R. Numerical Range and a Generalization of Duffin’s Overdamping Criterion (2024) Computational Mathematics and Mathematical Physics, 64 (4), pp. 599 - 604 Scopus DOI Q3

Savchuk, O., Puchinin, S., Stonyakin, F., Alkousa, M., Gasnikov, A. Numerical Methods for Variational Inequalities and Saddle Point Problems with Relative Inexact Information (2024) Communications in Computer and Information Science, 2239 CCIS, pp. 19-45. Scopus DOI Q4

Yudin, N.E., Gasnikov, A.V. Regularization and acceleration of Gauss - Newton method [Регуляризация и ускорение метода Гаусса - Ньютона] (2024) Computer Research and Modeling, 16 (7), pp. 1829-1840. Scopus DOI Q4

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

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

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

Aleksandr Lobanov, Alexander Gasnikov, Eduard Gorbunov, Martin Takáč. Linear Convergence Rate in Convex Setup is Possible! Gradient Descent Method Variants under (L_0,L_1)-Smoothness (2025) 

Ilya Kuruzov, Gesualdo Scutari, Alexander Gasnikov. Achieving linear convergence with parameter-free algorithms in decentralized optimization (2024) Advances in Neural Information Processing Systems

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

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. Gasnikov, V. Temlyakov. Some lower bounds for optimal sampling recovery of functions with mixed smoothness (2024)

V.N. Smirnov, K.M. Kazistova, I.A. Sudakov, V. Leplat, A.V. Gasnikov, A.V. Lobanov. Ruppert-Polyak averaging for Stochastic Order Oracle (2024)