Публикации

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

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