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Publications in Math-Net.Ru |
Citations |
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2023 |
| 1. |
F. S. Stonyakin, O. S. Savchuk, I. V. Baran, M. S. Alkousa, A. A. Titov, “Analogues of the relative strong convexity condition for relatively smooth problems and adaptive gradient-type methods”, Computer Research and Modeling, 15:2 (2023), 413–432  |
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2022 |
| 2. |
O. S. Savchuk, A. A. Titov, F. S. Stonyakin, M. S. Alkousa, “Adaptive first-order methods for relatively strongly convex optimization problems”, Computer Research and Modeling, 14:2 (2022), 445–472 |
| 3. |
F. S. Stonyakin, A. A. Titov, D. V. Makarenko, M. S. Alkousa, “Numerical Methods for Some Classes of Variational Inequalities with Relatively Strongly Monotone Operators”, Mat. Zametki, 112:6 (2022), 879–894  ; Math. Notes, 112:6 (2022), 965–977  |
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2020 |
| 4. |
F. S. Stonyakin, A. N. Stepanov, A. V. Gasnikov, A. A. Titov, “Mirror descent for constrained optimization problems with large subgradient values of functional constraints”, Computer Research and Modeling, 12:2 (2020), 301–317 |
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2019 |
| 5. |
F. S. Stonyakin, M. Alkousa, A. N. Stepanov, A. A. Titov, “Adaptive mirror descent algorithms for convex and strongly convex optimization problems with functional constraints”, Diskretn. Anal. Issled. Oper., 26:3 (2019), 88–114 ; J. Appl. Industr. Math., 13:3 (2019), 557–574 |
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| 6. |
A. V. Gasnikov, P. E. Dvurechenskii, F. S. Stonyakin, A. A. Titov, “An adaptive proximal method for variational inequalities”, Zh. Vychisl. Mat. Mat. Fiz., 59:5 (2019), 889–894  ; Comput. Math. Math. Phys., 59:5 (2019), 836–841  |
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