Калиниченко Виктория Константиновна · Publications

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

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

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

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*

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 Q1

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

Stonyakin F., Kuruzov I., Polyak B. Stopping Rules for Gradient Methods for Non-convex Problems with Additive Noise in Gradient (2023) Journal of Optimization Theory and Applications, 198 (2), pp. 531 - 551 Scopus DOI Q1

Gasnikova, E.V., Gasnikov, A.V., Yarmoshik, D.V., Kubentaeva, M.B., Persianov, M.I., Podlipnova, I.V., Kotlyarova, E.V., Sklonin, I.A., Podobnaya, E.D., Matyukhin, V.V. Multistage Transportation Model and Sufficient Conditions for Its Potentiality (2023) Doklady Mathematics, 108 (Suppl 1), pp. S139-S144. Scopus DOI Q1

Rudakov, M.I., Beznosikov, A.N., Kholodov, Y.A., Gasnikov, A.V. Activations and Gradients Compression for Model-Parallel Training (2024) Doklady Mathematics, 108 (Suppl 2), pp. S272-S281. Scopus DOI Q1

Medyakov, D., Molodtsov, G., Beznosikov, A., Gasnikov, A. Optimal Data Splitting in Distributed Optimization for Machine Learning (2023) Doklady Mathematics, 108 (Suppl 2), pp. S465-S475. Scopus DOI Q1

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