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ORCIDDmitry Kovalev
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2020 – today
- 2024
[j5]Dmitry Metelev, Alexander Rogozin, Alexander V. Gasnikov, Dmitry Kovalev
:
Decentralized saddle-point problems with different constants of strong convexity and strong concavity. Comput. Manag. Sci. 21(1): 5 (2024)- [j4]Olga Yufereva, Michael Persiianov, Pavel E. Dvurechensky, Alexander V. Gasnikov, Dmitry Kovalev:
Decentralized convex optimization on time-varying networks with application to Wasserstein barycenters. Comput. Manag. Sci. 21(1): 12 (2024) - [i26]Dmitry Kovalev, Ekaterina Borodich, Alexander V. Gasnikov, Dmitrii Feoktistov:
Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks. CoRR abs/2405.18031 (2024) - 2023
- [j3]Aleksandr V. Lobanov, Andrew Veprikov, Georgiy Konin, Aleksandr Beznosikov, Alexander V. Gasnikov, Dmitry Kovalev:
Non-smooth setting of stochastic decentralized convex optimization problem over time-varying Graphs. Comput. Manag. Sci. 20(1): 48 (2023) - [j2]Samuel Horváth, Dmitry Kovalev, Konstantin Mishchenko, Peter Richtárik, Sebastian U. Stich:
Stochastic distributed learning with gradient quantization and double-variance reduction. Optim. Methods Softw. 38(1): 91-106 (2023) - [c33]Dmitry Metelev, Alexander Rogozin, Dmitry Kovalev, Alexander V. Gasnikov:
Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks? ICML 2023: 24532-24554 - 2022
- [j1]Ekaterina Borodich, Vladislav Tominin, Yaroslav Tominin, Dmitry Kovalev, Alexander V. Gasnikov, Pavel E. Dvurechensky:
Accelerated variance-reduced methods for saddle-point problems. EURO J. Comput. Optim. 10: 100048 (2022) - [c32]Adil Salim, Laurent Condat, Dmitry Kovalev, Peter Richtárik:
An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints. AISTATS 2022: 4482-4498 - [c31]Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtárik:
IntSGD: Adaptive Floatless Compression of Stochastic Gradients. ICLR 2022 - [c30]Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich, Alexander V. Gasnikov, Gesualdo Scutari:
Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity. NeurIPS 2022 - [c29]Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov:
Optimal Algorithms for Decentralized Stochastic Variational Inequalities. NeurIPS 2022 - [c28]Dmitry Kovalev, Alexander V. Gasnikov:
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization. NeurIPS 2022 - [c27]Dmitry Kovalev, Alexander V. Gasnikov:
The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization. NeurIPS 2022 - [c26]Dmitry Kovalev, Alexander V. Gasnikov, Peter Richtárik:
Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling. NeurIPS 2022 - [c25]Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtárik:
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox. NeurIPS 2022 - [i25]Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov:
Optimal Algorithms for Decentralized Stochastic Variational Inequalities. CoRR abs/2202.02771 (2022) - [i24]Evgenia Romanenkova, Alina Rogulina, Anuar Shakirov, Nikolay Stulov, Alexey Zaytsev, Leyla S. Ismailova, Dmitry Kovalev, Klemens Katterbauer, Abdallah A. AlShehri:
Similarity learning for wells based on logging data. CoRR abs/2202.05583 (2022) - [i23]Dmitry Kovalev, Alexander V. Gasnikov:
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization. CoRR abs/2205.05653 (2022) - [i22]Dmitry Kovalev, Alexander V. Gasnikov:
The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization. CoRR abs/2205.09647 (2022) - [i21]Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich, Alexander V. Gasnikov, Gesualdo Scutari:
Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity. CoRR abs/2205.15136 (2022) - [i20]Aleksandr Beznosikov, Aibek Alanov, Dmitry Kovalev, Martin Takác, Alexander V. Gasnikov:
On Scaled Methods for Saddle Point Problems. CoRR abs/2206.08303 (2022) - [i19]Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtárik:
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with Inexact Prox. CoRR abs/2207.03957 (2022) - [i18]Aleksandr Beznosikov, Boris T. Polyak, Eduard Gorbunov, Dmitry Kovalev, Alexander V. Gasnikov:
Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems - Survey. CoRR abs/2208.13592 (2022) - [i17]Dmitry Kovalev, Alexander V. Gasnikov, Grigory Malinovsky:
An Optimal Algorithm for Strongly Convex Min-min Optimization. CoRR abs/2212.14439 (2022) - 2021
- [c24]Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtárik, Sebastian U. Stich:
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! AISTATS 2021: 4087-4095 - [c23]Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander V. Gasnikov:
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. ICML 2021: 5784-5793 - [c22]Dmitry Kovalev, Elnur Gasanov, Alexander V. Gasnikov, Peter Richtárik:
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks. NeurIPS 2021: 22325-22335 - [c21]Aleksandr Beznosikov, Alexander Rogozin, Dmitry Kovalev, Alexander V. Gasnikov:
Near-Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks. OPTIMA 2021: 246-257 - [c20]Alexander Rogozin, Vladislav Lukoshkin, Alexander V. Gasnikov, Dmitry Kovalev, Egor Shulgin:
Towards Accelerated Rates for Distributed Optimization over Time-Varying Networks. OPTIMA 2021: 258-272 - [c19]Dmitry Kovalev, Dmitry Khliustov, Sergey O. Safonov:
Comparison of Data-Driven Approaches to Modeling Complex Behavior of 2D Liquid Simulator. DAMDID/RCDL (Supplementary Proceedings) 2021: 94-109 - [i16]Alexander Rogozin, Aleksandr Beznosikov, Darina Dvinskikh, Dmitry Kovalev, Pavel E. Dvurechensky, Alexander V. Gasnikov:
Decentralized Distributed Optimization for Saddle Point Problems. CoRR abs/2102.07758 (2021) - [i15]Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtárik:
IntSGD: Floatless Compression of Stochastic Gradients. CoRR abs/2102.08374 (2021) - [i14]Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander V. Gasnikov:
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. CoRR abs/2102.09234 (2021) - [i13]Dmitry Kovalev, Elnur Gasanov, Peter Richtárik, Alexander V. Gasnikov:
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks. CoRR abs/2106.04469 (2021) - [i12]Dmitry Kovalev, Alexander V. Gasnikov, Peter Richtárik:
Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling. CoRR abs/2112.15199 (2021) - 2020
- [c18]Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky:
Revisiting Stochastic Extragradient. AISTATS 2020: 4573-4582 - [c17]Dmitry Kovalev, Samuel Horváth, Peter Richtárik:
Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop. ALT 2020: 451-467 - [c16]Filip Hanzely, Dmitry Kovalev, Peter Richtárik:
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems. ICML 2020: 4039-4048 - [c15]Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik:
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. ICML 2020: 5895-5904 - [c14]Grigory Malinovskiy, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtárik:
From Local SGD to Local Fixed-Point Methods for Federated Learning. ICML 2020: 6692-6701 - [c13]Andrey Kovalev, Dmitriy Kovalev, Vladimir Panchenko, Valeriy Kharchenko, Pandian Vasant:
Intellectualized Control System of Technological Processes of an Experimental Biogas Plant with Improved System for Preliminary Preparation of Initial Waste. ICO 2020: 1186-1194 - [c12]Andrey Kovalev, Dmitriy Kovalev, Vladimir Panchenko, Valeriy Kharchenko, Pandian Vasant:
Way for Intensifying the Process of Anaerobic Bioconversion by Preliminary Hydrolysis and Increasing Solid Retention Time. ICO 2020: 1195-1203 - [c11]Eduard Gorbunov, Dmitry Kovalev, Dmitry Makarenko, Peter Richtárik:
Linearly Converging Error Compensated SGD. NeurIPS 2020 - [c10]Dmitry Kovalev, Adil Salim, Peter Richtárik:
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization. NeurIPS 2020 - [c9]Dmitriy Kovalev, Egor Tirikov, Dmitrii Sergeev, Natalya V. Ponomareva:
Методы и средства анализа сигналов головного мозга человека на данных функциональной магнитно-резонансной томографии (Methods and Tools for the Human Brain Signals Analysis over the Functional Magnetic Resonance Imaging Data). DAMDID/RCDL (Supplementary Proceedings) 2020: 214-229 - [i11]Filip Hanzely, Dmitry Kovalev, Peter Richtárik:
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems. CoRR abs/2002.04670 (2020) - [i10]Dmitry Kovalev, Robert M. Gower, Peter Richtárik, Alexander Rogozin:
Fast Linear Convergence of Randomized BFGS. CoRR abs/2002.11337 (2020) - [i9]Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik:
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. CoRR abs/2002.11364 (2020) - [i8]Grigory Malinovsky, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtárik:
From Local SGD to Local Fixed Point Methods for Federated Learning. CoRR abs/2004.01442 (2020) - [i7]Eduard Gorbunov, Dmitry Kovalev, Dmitry Makarenko, Peter Richtárik:
Linearly Converging Error Compensated SGD. CoRR abs/2010.12292 (2020) - [i6]Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtárik, Sebastian U. Stich:
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! CoRR abs/2011.01697 (2020)
2010 – 2019
- 2019
- [c8]Andrey Kovalev, Dmitriy Kovalev, Vladimir Panchenko, Valeriy Kharchenko, Pandian Vasant:
Optimization of the Process of Anaerobic Bioconversion of Liquid Organic Wastes. ICO 2019: 170-176 - [c7]Andrey Kovalev, Dmitriy Kovalev, Vladimir Panchenko, Valeriy Kharchenko, Pandian Vasant:
System of Optimization of the Combustion Process of Biogas for the Biogas Plant Heat Supply. ICO 2019: 361-368 - [c6]Robert M. Gower, Dmitry Kovalev, Felix Lieder, Peter Richtárik:
RSN: Randomized Subspace Newton. NeurIPS 2019: 614-623 - [c5]Adil Salim, Dmitry Kovalev, Peter Richtárik:
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates. NeurIPS 2019: 6649-6661 - [i5]Dmitry Kovalev, Samuel Horváth, Peter Richtárik:
Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop. CoRR abs/1901.08689 (2019) - [i4]Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky:
Revisiting Stochastic Extragradient. CoRR abs/1905.11373 (2019) - [i3]Adil Salim, Dmitry Kovalev, Peter Richtárik:
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates. CoRR abs/1905.11768 (2019) - [i2]Dmitry Kovalev, Konstantin Mishchenko, Peter Richtárik:
Stochastic Newton and Cubic Newton Methods with Simple Local Linear-Quadratic Rates. CoRR abs/1912.01597 (2019) - [i1]Sélim Chraibi, Ahmed Khaled, Dmitry Kovalev, Peter Richtárik, Adil Salim, Martin Takác:
Distributed Fixed Point Methods with Compressed Iterates. CoRR abs/1912.09925 (2019) - 2018
- [c4]Dmitry Kovalev, Peter Richtárik, Eduard Gorbunov, Elnur Gasanov:
Stochastic Spectral and Conjugate Descent Methods. NeurIPS 2018: 3362-3371 - 2017
- [c3]Dmitry Kovalev, Sergey Priimenko, Natalya V. Ponomareva:
Search for Gender Difference in Functional Connectivity of Resting State fMRI. DAMDID/RCDL 2017: 150-156 - [c2]Evgeny Tarasov, Dmitry Kovalev:
Оценка качества научных гипотез в виртуальных экспериментах в областях с интенсивным использованием данных (Estimation of Scientific Hypotheses Quality in Virtual Experiments in Data Intensive Domains). DAMDID/RCDL 2017: 281-292 - 2013
- [c1]Dmitry Kovalev:
Декларативная аналитика в мультидиалектной среде (Declarative Analytics in Multidialect Infrastructure). RCDL 2013: 202-207
Coauthor Index
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