2022

[20] Gladin E.L., Kuruzov I.A., Pasechnyuk D.A., Stonyakin F.S., Alkousa M.S., Gasnikov A.V. Solving strongly convex-concave composite saddle point problems with a small dimension of one of the variables. Sbornik: Mathematics (2022) URL https://arxiv.org/abs/2010.02280

[19] Ivanova, A., Dvurechensky, P., Vorontsova, E., Pasechnyuk, D., Gasnikov, A., Dvinskikh, D., Tyurin, A.: Oracle Complexity Separation in Convex Optimization. Journal of Optimization Theory and Applications (2022). DOI 10.1007/s10957-022-02038-7

[18] Alpatov A.V., Peters E.A., Pasechnyuk D.A., Raigorodskii A.M.: Stochastic optimization in digital pre-distortion of the signal. Computer Research and Modeling 14(2), 399–416 (2022) DOI 10.20537/2076-7633-2022-14-2-399-416

[17] Beznosikov A.N., Gasnikov A.V., Zainullina K.E., Maslovskiy A.Yu., Pasechnyuk D.A.: A Unified Analysis of Variational Inequality Methods: Variance Reduction, Sampling, Quantization and Coordinate Descent. Computational Mathematics and Mathematical Physics (2022) URL https://arxiv.org/abs/2201.12206

[16] Pasechnyuk D.A., Anikin A.S., Matyukhin V.V.: Accelerated Proximal Envelopes: Application to the Coordinate Descent Method. Computational Mathematics and Mathematical Physics 62(2), 342–352 (2022) DOI 10.1134/S0965542522020038

[15] Pasechnyuk, D., Gornov, A.: Solar method for non-convex problems: hypothesizing approach to an optimization. Preprint (2022). URL http://dmivilensky.ru/preprints/Solar%20method%20for%20non-convex%20problems.pdf

2021

[14] Stonyakin, F., Titov, A., Alkousa, M., Savchuk, O., Pasechnyuk, D.: Gradient-type adaptive methods for relatively Lipschitz convex optimization problems. Preprint (2021). URL https://arxiv.org/abs/2107.05765

[13] Pasechnyuk, D., Raigorodskii, A.: Network utility maximization by updating individual transmission rates. International Conference on Optimization and Applications. Communications in Computer and Information Science 1514, 184–198. Springer, Cham (2021). DOI 10.1007/978-3-030-92711-0_13

[12] Pasechnyuk, D., Dvurechensky, P., Omelchenko, S., Gasnikov, A.: Stochastic optimization for dynamic pricing. International Conference on Optimization and Applications. Communications in Computer and Information Science 1514, 82–94. Springer, Cham (2021). DOI 10.1007/978-3-030-92711-0_6

[11] Pasechnyuk, D., Matyukhin, V.: On the Computational Efficiency of Catalyst Accelerated Coordinate Descent. International Conference on Mathematical Optimization Theory and Operations Research. Lecture Notes in Computer Science 12755, 176–191. Springer, Cham (2021). DOI 10.1007/978-3-030-77876-7_12

[10] Pasechnyuk, D., Maslovskiy, A., Gasnikov, A., Anikin, A., Rogozin, A., Gornov, A., Vorobyev, A., Antonov, L., Vlasov, R., Nikolaeva, A., Yanitskiy, E., Begicheva, M.: Non-convex optimization in digital pre-distortion of the signal. International Conference on Mathematical Optimization Theory and Operations Research. Communications in Computer and Information Science 1476, 54–70. Springer, Cham (2021). DOI 10.1007/978-3-030-86433-0_4

[9] Gasnikov A.V., Dvinskikh D.M., Dvurechensky P.E., Kamzolov D.I., Matyukhin V.V., Pasechnyuk D.A., Tupitsa N.K., Chernov A.V. Accelerated meta-algorithm for convex optimization. Computational Mathematics and Mathematical Physics 61(1), 17–28 (2021) DOI 10.1134/S096554252101005X

[8] Ivanova, A., Pasechnyuk, D., Grishchenko, D., Shulgin, E., Gasnikov, A., Matyukhin, V.: Adaptive catalyst for smooth convex optimization. International Conference on Optimization and Applications. Lecture Notes in Computer Science 13078, 20–37. Springer, Cham (2021). DOI 10.1007/978-3-030-91059-4_2

[7] Ivanova A.S., Pasechnyuk D.A., Dvurechensky P.E., Gasnikov A.V., Vorontsova E.A.: Numerical methods for the resource allocation problem in networks. Computational Mathematics and Mathematical Physics 61(2), 312–345 (2021) DOI 10.1134/S0965542521020135

[6] 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. Optimization Methods and Software, 1–47 (2021). DOI 10.1080/10556788.2021.1924714

2020

[5] Ivanova, A., Stonyakin, F., Pasechnyuk, D., Vorontsova, E., Gasnikov, A.: Adaptive Mirror Descent for the Network Utility Maximization Problem. IFAC-PapersOnLine 53(2), 7851–7856 (2020). DOI 10.1016/j.ifacol.2020.12.1958

2019

[4] Stonyakin, F., Gasnikov, A., Tyurin, A., Pasechnyuk, D., Agafonov, A., Dvurechensky, P., Dvinskikh, D., Kroshnin, A., Piskunova, V.: Inexact model: A framework for optimization and variational inequalities. Preprint (2019). URL https://arxiv.org/abs/1902.00990

[3] Pasechnyuk D.A., Stonyakin F.S.: One method for minimization a convex Lipschitz-continuous function of two variables on a fixed square. Computer Research and Modeling 11(3), 379–395 (2019) DOI 10.20537/2076-7633-2019-11-3-379-395

[2] Stonyakin, F., Dvinskikh, D., Dvurechensky, P., Kroshnin, A., Kuznetsova, O., Agafonov, A., Gasnikov, A., Tyurin, A., Uribe, C., Pasechnyuk, D., Artamonov, S.: Gradient methods for problems with inexact model of the objective. International Conference on Mathematical Optimization Theory and Operations Research. Lecture Notes in Computer Science 11548, 97–114. Springer, Cham (2019). DOI 10.1007/978-3-030-22629-9_8

[1] Pasechnyuk D.A.: Scheduling strategies for resource allocation in a cellular base station. Proceedings of MIPT 11(2), 38–48 (2019) URL https://mipt.ru/upload/medialibrary/f16/4_trudy-mfti-_2_42_38_48.pdf

2021

Report "Solar" method: a two-level algorithm in a one-level optimization problem Lyapunov reading, ISDCT SB RAS (2021). URL https://ris.icc.ru/publications/6158

Lection Optimization in SE. JetBrains Research, ML4SE lab (2021). URL https://youtu.be/bzGWnhb8_-8

Reports Stochastic optimization for dynamic pricing, Network utility maximization by updating individual transmission rates and Adaptive catalyst for smooth convex optimization. International Conference Optimization and Applications (2021). URL http://agora.guru.ru/display.php

Reports Network utility maximization: optimization & protocols and Full-gradient based methods for modeling nonlinear systems in digital signal processing. Optimization without borders (2021). URL http://dmivilensky.ru/opt_without_borders/

Report On the Computational Efficiency of Catalyst Accelerated Coordinate Descent. International Conference Mathematical Optimization Theory and Operations Research (2021). URL https://easychair.org/smart-program/MOTOR2021/

2020

Report Universal Accelerated Proximal Envelopes. The 63rd MIPT Scientific Conference (2020). URL https://conf.mipt.ru//folders/attachment/2882/download

Report Accelerated Proximal Envelopes: Application to the Coordinate Descent Method. School Modern Methods of Information Theory, Optimization and Control, Sirius University (2020). URL https://sochisirius.ru/obuchenie/graduates/smena673/3259

2019

Poster On Inexactness for Yu.E. Nesterov Method for a Convex Minimization on a Fixed Square. Traditional School for Young Researchers Control, Information, Optimization (2019). URL https://ssopt.org/2019

Report On Inexactness for Yu.E. Nesterov Method for a Convex Minimization on a Fixed Square. Conference on graphs, networks, and their applications, MIPT (2019). URL http://ru.discrete-mathematics.org/conferences/201905/workshop_graphs/schedule_workshop_network_optimization.pdf

2018

Report Throughput maximization for flows with fine input structure. Workshop Optimization at Work, MIPT (2018). URL http://www.mathnet.ru/php/conference.phtml?eventID=1&confid=1259

2017

Report Index Strategies for Routing Base Station Traffic. The 60th MIPT Scientific Conference (2017). URL https://abitu.net/public/admin/mipt-conference/FPMI.pdf