Pavel Dvurechensky
- Senior Research Fellow:Faculty of Computer Science / International Laboratory of Stochastic Algorithms and High-Dimensional Inference
- Pavel Dvurechensky has been at HSE University since 2017.
Education and Degrees
- 2013
Candidate of Sciences* (PhD)
- 2010
Master's in Applied Mathematics and Physics
Moscow Institute of Physics and Technology
According to the International Standard Classification of Education (ISCED) 2011, Candidate of Sciences belongs to ISCED level 8 - "doctoral or equivalent", together with PhD, DPhil, D.Lit, D.Sc, LL.D, Doctorate or similar. Candidate of Sciences allows its holders to reach the level of the Associate Professor.
Courses (2020/2021)
Publications26
- Article Dvurechensky P., Eduard Gorbunov, Gasnikov A. An accelerated directional derivative method for smooth stochastic convex optimization // European Journal of Operational Research. 2021. Vol. 290. No. 2. P. 601-621. doi
- Chapter Dvurechensky P., Gasnikov A., Omelchenko S., Tyurin A. A Stable Alternative to Sinkhorn’s Algorithm for Regularized Optimal Transport, in: Mathematical Optimization Theory and Operations Research, 19th International Conference, MOTOR 2020, Novosibirsk, Russia, July 6–10, 2020, (Т. 12095) / Ed. by A. Kononov, M. Khachay, P. Pardalos, V. A. Kalyagin. Cham : Springer, 2020. doi P. 406-423. doi
- Chapter Dvurechensky P., Gasnikov A., Nurminski E., Stonyakin F. Advances in Low-Memory Subgradient Optimization, in: Numerical Nonsmooth Optimization. Springer, 2020. doi P. 19-59. doi
- Article Ivanova A., Dvurechensky P., Gasnikov A., Kamzolov D. Composite optimization for the resource allocation problem // Optimization Methods and Software. 2020. P. 1-35. doi (in press)
- Chapter Tupitsa, N., Dvurechensky P., Gasnikov A., Uribe C. A. Multimarginal Optimal Transport by Accelerated Alternating Minimization, in: 2020 IEEE 59th Conference on Decision and Control (CDC). IEEE, 2020. doi P. 6132-6137. doi
- Preprint Dvurechensky P., Gasnikov A., Остроухов П., Uribe C., Ivanova A. Near-optimal tensor methods for minimizing the gradient norm of convex function / Working papers by Cornell University.. Series - "Optimization and Control". 2020. (in press)
- Preprint Ivanova A., Gasnikov A., Dvurechensky P., Двинских Д., Тюрин А. И., Воронцова Е., Пасечнюк Д. Oracle Complexity Separation in Convex Optimization / Working papers by Cornell University.. Series - "Optimization and Control". 2020. (in press)
- Article Gasnikov A., Dvurechensky P. Primal–dual accelerated gradient methods with small-dimensional relaxation oracle // Optimization Methods and Software. 2020. P. 1-38. doi (in press)
- Chapter Dvurechensky P., Ostroukhov P., Safin K., Shtern S., Staudigl M. Self-concordant analysis of Frank-Wolfe algorithms, in: International Conference on Machine Learning (ICML 2020) Vol. 119. PMLR, 2020. (in press)
- Chapter Tupitsa N., Gasnikov A., Dvurechensky P., Guminov S. Strongly Convex Optimization for the Dual Formulation of Optimal Transport, in: Mathematical Optimization Theory and Operations Research. MOTOR 2020. Communications in Computer and Information Science Vol. 1275. Springer, 2020. doi P. 192-204. doi
- Article Gasnikov A., Dvurechensky P. Universal intermediate gradient method for convex problems with inexact oracle // Optimization Methods and Software. 2020. P. 1-28. doi (in press)
- Article Guminov S., Nesterov Y., Dvurechensky P., Gasnikov A. Accelerated primal-dual gradient descent with linesearch for convex, nonconvex, and nonsmooth optimization problems / Пер. с рус. // Doklady Mathematics. 2019. Vol. 99. No. 2. P. 125-128. doi
- Article Gasnikov A., Dvurechensky P., Stonyakin F. S., Titov A. An Adaptive Proximal Method for Variational Inequalities // Computational Mathematics and Mathematical Physics. 2019. Vol. 59. P. 836-841. doi
- Chapter 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, in: Mathematical Optimization Theory and Operations Research, 18th International Conference, MOTOR 2019 Ekaterinburg, Russia, July 8–12, 2019 / Ed. by М. Ю. Хачай, Ю. А. Кочетов, P. M. Pardalos. Vol. 11548. Springer, 2019. P. 97-114. doi
- Chapter Gasnikov A., Gorbunov E., Dvurechensky P., Vorontsova E., Selikhanovich D., Uribe C., Jiang B., Haoyue W. Near Optimal Methods for Minimizing Convex Functions with Lipschitz p-th Derivatives, in: Proceedings of Machine Learning Research Vol. 99: Conference on Learning Theory, 25-28 June 2019, Phoenix, AZ, USA. PMLR, 2019.. PMLR, 2019. P. 1392-1393.
- Preprint Иванова А. С., Пасечнюк Д., Двуреченский П. Е., Гасников А. В., Воронцова Е. Numerical methods for the resource allocation problem in networks / Cornell University. Серия "Working papers by Cornell University". 2019. (in press)
- Chapter Dvinskikh D., Gorbunov E., Gasnikov A., Dvurechensky P., Uribe C. On Primal and Dual Approaches for Distributed Stochastic Convex Optimization over Networks, in: 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019. doi P. 7435-7440. doi
- Chapter Kroshnin A., Dvinskikh D., Dvurechensky P., Gasnikov Alexander, Tupitsa Nazarii, Uribe C. A. On the Complexity of Approximating Wasserstein Barycenters, in: Proceedings of Machine Learning Research Vol. 97: International Conference on Machine Learning, 9-15 June 2019, Long Beach, California, USA. PMLR, 2019. P. 3530-3540.
- Chapter Gasnikov A., Dvurechensky P., Gorbunov E., Vorontsova E., Selikhanovych D., Uribe C. Optimal Tensor Methods in Smooth Convex and Uniformly Convex Optimization, in: Conference on Learning Theory, 25-28 June 2019, Phoenix, USA Vol. 99. , 2019. P. 1374-1391.
- Article Baimurzina D., Gasnikov A., Dvurechensky P., Ershov E., Kubentaeva M., Lagunovskaya A. Universal Method of Searching for Equilibria and Stochastic Equilibria in Transportation Networks // Computational Mathematics and Mathematical Physics. 2019. Vol. 59. No. 1. P. 19-33. doi
- Article Воронцова Е. А., Гасников А. В., Горбунов Э. А., Двуреченский П. Е. Ускоренные безградиентные методы оптимизации с неевклидовым проксимальным оператором // Автоматика и телемеханика. 2019. № 8. С. 149-168. doi
- Chapter Dvurechensky P., Gasnikov A., Kroshnin A. Computational optimal transport: Complexity by accelerated gradient descent is better than by Sinkhorn's algorithm, in: Proceedings of the 35th International Conference on Machine Learning (2018) Vol. 80. PMLR, 2018. P. 1367-1376.
- Chapter Dvurechensky P., Dvinskikh D., Gasnikov A., Uribe C., Nedic A. Decentralize and randomize: Faster algorithm for Wasserstein barycenters, in: Advances in Neural Information Processing Systems 31 (NeurIPS 2018). Neural Information Processing Systems Foundation, 2018. P. 10760-10770.
- Chapter Bayandina A., Dvurechensky P., Gasnikov A., Stonyakin F. S., Titov A. Mirror Descent and Convex Optimization Problems with Non-smooth Inequality Constraints, in: Large-Scale and Distributed Optimization Vol. 2227. Springer, 2018. doi P. 181-213. doi
- Chapter Bogolubsky L., Dvurechensky P., Gasnikov A., Gusev G., Nesterov Y., Raigorodsky A., Tikhonov A., Zhukovskii M. Learning supervised pagerank with gradient-based and gradient-free optimization methods, in: Advances in Neural Information Processing Systems 29 (NIPS 2016). NY : Curran Associates, 2016. P. 4914-4922.
- Article Dvurechensky P., Gasnikov A. Stochastic intermediate gradient method for convex problems with stochastic inexact oracle // Journal of Optimization Theory and Applications. 2016. Vol. 171. No. 1. P. 121-145. doi
Employment history
2015–now. Research fellow (PostDoc), Weierstrass Institute for Applied Analysis and Stochastics,
Research Group 6 "Stochastic Algorithms and Nonparametric Statistics", Berlin,
Germany.
2014–2015. Researcher (PostDoc), Institute for Information Transmission Problems, sector 7
of Mathematical Methods of Predictive Modeling, Moscow, Russia
2012–2015. Junior researcher, Moscow Institute of Physics and Technology (MIPT), Laboratory
of Structural Methods of Data Analysis in Predictive Modeling (PreMoLab), Moscow,
Russia.
HSE University Becomes the First Russian University to Confer a Doctoral Degree in Computer Science
Upon successfully defending his dissertation before HSE Dissertation Council in Computer Science, Pavel Dvurechensky became the first Doctor of Computer Science in Russia. This was possible thanks to the fact that, starting in 2018, HSE University received the right to award its own academic degrees.