Dmitry Kovalev

70 papers A* 21A 4B 1Journal 38Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	An Optimal Algorithm for Strongly Convex Min-Min Optimization. UAI Dmitry Kovalev, Alexander V. Gasnikov, Grigory Malinovsky
2025	A*	`conf`	Decentralized Optimization with Coupled Constraints. ICLR Demyan Yarmoshik, Alexander Rogozin, Nikita Kiselev, Daniil Dorin, Alexander V. Gasnikov, Dmitry Kovalev
2025	J	`jnl`	Decentralized saddle point problems via non-Euclidean mirror prox. Optim. Methods Softw. Alexander Rogozin, Aleksandr Beznosikov, Darina Dvinskikh, Dmitry Kovalev, Pavel E. Dvurechensky, Alexander V. Gasnikov
2025	J	`jnl`	Muon is Provably Faster with Momentum Variance Reduction. CoRR Xun Qian, Hussein Rammal, Dmitry Kovalev, Peter Richtárik
2025	J	`jnl`	Nesterov Finds GRAAL: Optimal and Adaptive Gradient Method for Convex Optimization. CoRR Ekaterina Borodich, Dmitry Kovalev
2025	J	`jnl`	Non-Euclidean SGD for Structured Optimization: Unified Analysis and Improved Rates. CoRR Dmitry Kovalev, Ekaterina Borodich
2025	A*	`conf`	On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms. ICML Ekaterina Borodich, Alexander V. Gasnikov, Dmitry Kovalev
2025	J	`jnl`	SGD with Adaptive Preconditioning: Unified Analysis and Momentum Acceleration. CoRR Dmitry Kovalev
2025	J	`jnl`	Understanding Gradient Orthogonalization for Deep Learning via Non-Euclidean Trust-Region Optimization. CoRR Dmitry Kovalev
2024	J	`jnl`	Decentralized convex optimization on time-varying networks with application to Wasserstein barycenters. Comput. Manag. Sci. Olga Yufereva, Michael Persiianov, Pavel E. Dvurechensky, Alexander V. Gasnikov, Dmitry Kovalev
2024	J	`jnl`	Decentralized saddle-point problems with different constants of strong convexity and strong concavity. Comput. Manag. Sci. Dmitry Metelev, Alexander Rogozin, Alexander V. Gasnikov, Dmitry Kovalev
2024	A*	`conf`	Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks. NeurIPS Dmitry Kovalev, Ekaterina Borodich, Alexander V. Gasnikov, Dmitrii Feoktistov
2024	J	`jnl`	Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks. CoRR Dmitry Kovalev, Ekaterina Borodich, Alexander V. Gasnikov, Dmitrii Feoktistov
2024	J	`jnl`	On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms. CoRR Dmitry Kovalev, Ekaterina Borodich
2023	A*	`conf`	Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks? ICML Dmitry Metelev, Alexander Rogozin, Dmitry Kovalev, Alexander V. Gasnikov
2023	J	`jnl`	Non-smooth setting of stochastic decentralized convex optimization problem over time-varying Graphs. Comput. Manag. Sci. Aleksandr V. Lobanov, Andrew Veprikov, Georgiy Konin, Aleksandr Beznosikov, Alexander V. Gasnikov, Dmitry Kovalev
2023	J	`jnl`	Stochastic distributed learning with gradient quantization and double-variance reduction. Optim. Methods Softw. Samuel Horváth, Dmitry Kovalev, Konstantin Mishchenko, Peter Richtárik, Sebastian U. Stich
2022	A*	`conf`	Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling. NeurIPS Dmitry Kovalev, Alexander V. Gasnikov, Peter Richtárik
2022	J	`jnl`	Accelerated variance-reduced methods for saddle-point problems. EURO J. Comput. Optim. Ekaterina Borodich, Vladislav Tominin, Yaroslav Tominin, Dmitry Kovalev, Alexander V. Gasnikov, Pavel E. Dvurechensky
2022	J	`jnl`	An Optimal Algorithm for Strongly Convex Min-min Optimization. CoRR Dmitry Kovalev, Alexander V. Gasnikov, Grigory Malinovsky
2022	A	`conf`	An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints. AISTATS Adil Salim, Laurent Condat, Dmitry Kovalev, Peter Richtárik
2022	J	`jnl`	Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with Inexact Prox. CoRR Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtárik
2022	A*	`conf`	Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox. NeurIPS Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtárik
2022	A*	`conf`	IntSGD: Adaptive Floatless Compression of Stochastic Gradients. ICLR Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtárik
2022	J	`jnl`	On Scaled Methods for Saddle Point Problems. CoRR Aleksandr Beznosikov, Aibek Alanov, Dmitry Kovalev, Martin Takác, Alexander V. Gasnikov
2022	A*	`conf`	Optimal Algorithms for Decentralized Stochastic Variational Inequalities. NeurIPS Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov
2022	J	`jnl`	Optimal Algorithms for Decentralized Stochastic Variational Inequalities. CoRR Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov
2022	J	`jnl`	Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity. CoRR Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich, Alexander V. Gasnikov, Gesualdo Scutari
2022	A*	`conf`	Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity. NeurIPS Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich, Alexander V. Gasnikov, Gesualdo Scutari
2022	J	`jnl`	Similarity learning for wells based on logging data. CoRR Evgenia Romanenkova, Alina Rogulina, Anuar Shakirov, Nikolay Stulov, Alexey Zaytsev, Leyla S. Ismailova, Dmitry Kovalev, Klemens Katterbauer, Abdallah A. AlShehri
2022	J	`jnl`	Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems - Survey. CoRR Aleksandr Beznosikov, Boris T. Polyak, Eduard Gorbunov, Dmitry Kovalev, Alexander V. Gasnikov
2022	A*	`conf`	The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization. NeurIPS Dmitry Kovalev, Alexander V. Gasnikov
2022	J	`jnl`	The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization. CoRR Dmitry Kovalev, Alexander V. Gasnikov
2022	A*	`conf`	The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization. NeurIPS Dmitry Kovalev, Alexander V. Gasnikov
2022	J	`jnl`	The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization. CoRR Dmitry Kovalev, Alexander V. Gasnikov
2021	A	`conf`	A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! AISTATS Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtárik, Sebastian U. Stich
2021	A*	`conf`	ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. ICML Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander V. Gasnikov
2021	J	`jnl`	ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. CoRR Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander V. Gasnikov
2021	J	`jnl`	Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling. CoRR Dmitry Kovalev, Alexander V. Gasnikov, Peter Richtárik
2021	—	`conf`	Comparison of Data-Driven Approaches to Modeling Complex Behavior of 2D Liquid Simulator. DAMDID/RCDL (Supplementary Proceedings) Dmitry Kovalev, Dmitry Khliustov, Sergey O. Safonov
2021	J	`jnl`	Decentralized Distributed Optimization for Saddle Point Problems. CoRR Alexander Rogozin, Aleksandr Beznosikov, Darina Dvinskikh, Dmitry Kovalev, Pavel E. Dvurechensky, Alexander V. Gasnikov
2021	J	`jnl`	IntSGD: Floatless Compression of Stochastic Gradients. CoRR Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtárik
2021	A*	`conf`	Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks. NeurIPS Dmitry Kovalev, Elnur Gasanov, Alexander V. Gasnikov, Peter Richtárik
2021	J	`jnl`	Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks. CoRR Dmitry Kovalev, Elnur Gasanov, Peter Richtárik, Alexander V. Gasnikov
2021	—	`conf`	Near-Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks. OPTIMA Aleksandr Beznosikov, Alexander Rogozin, Dmitry Kovalev, Alexander V. Gasnikov
2021	—	`conf`	Towards Accelerated Rates for Distributed Optimization over Time-Varying Networks. OPTIMA Alexander Rogozin, Vladislav Lukoshkin, Alexander V. Gasnikov, Dmitry Kovalev, Egor Shulgin
2020	J	`jnl`	A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! CoRR Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtárik, Sebastian U. Stich
2020	A*	`conf`	Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. ICML Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik
2020	J	`jnl`	Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. CoRR Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik
2020	B	`conf`	Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop. ALT Dmitry Kovalev, Samuel Horváth, Peter Richtárik
2020	J	`jnl`	Fast Linear Convergence of Randomized BFGS. CoRR Dmitry Kovalev, Robert M. Gower, Peter Richtárik, Alexander Rogozin
2020	J	`jnl`	From Local SGD to Local Fixed Point Methods for Federated Learning. CoRR Grigory Malinovsky, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtárik
2020	A*	`conf`	From Local SGD to Local Fixed-Point Methods for Federated Learning. ICML Grigory Malinovskiy, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtárik
2020	A*	`conf`	Linearly Converging Error Compensated SGD. NeurIPS Eduard Gorbunov, Dmitry Kovalev, Dmitry Makarenko, Peter Richtárik
2020	J	`jnl`	Linearly Converging Error Compensated SGD. CoRR Eduard Gorbunov, Dmitry Kovalev, Dmitry Makarenko, Peter Richtárik
2020	A*	`conf`	Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization. NeurIPS Dmitry Kovalev, Adil Salim, Peter Richtárik
2020	A	`conf`	Revisiting Stochastic Extragradient. AISTATS Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky
2020	A*	`conf`	Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems. ICML Filip Hanzely, Dmitry Kovalev, Peter Richtárik
2020	J	`jnl`	Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems. CoRR Filip Hanzely, Dmitry Kovalev, Peter Richtárik
2019	J	`jnl`	Distributed Fixed Point Methods with Compressed Iterates. CoRR Sélim Chraibi, Ahmed Khaled, Dmitry Kovalev, Peter Richtárik, Adil Salim, Martin Takác
2019	J	`jnl`	Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop. CoRR Dmitry Kovalev, Samuel Horváth, Peter Richtárik
2019	A*	`conf`	RSN: Randomized Subspace Newton. NeurIPS Robert M. Gower, Dmitry Kovalev, Felix Lieder, Peter Richtárik
2019	J	`jnl`	Revisiting Stochastic Extragradient. CoRR Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky
2019	J	`jnl`	Stochastic Newton and Cubic Newton Methods with Simple Local Linear-Quadratic Rates. CoRR Dmitry Kovalev, Konstantin Mishchenko, Peter Richtárik
2019	A*	`conf`	Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates. NeurIPS Adil Salim, Dmitry Kovalev, Peter Richtárik
2019	J	`jnl`	Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates. CoRR Adil Salim, Dmitry Kovalev, Peter Richtárik
2018	A*	`conf`	Stochastic Spectral and Conjugate Descent Methods. NeurIPS Dmitry Kovalev, Peter Richtárik, Eduard Gorbunov, Elnur Gasanov
2017	—	`conf`	Search for Gender Difference in Functional Connectivity of Resting State fMRI. DAMDID/RCDL Dmitry Kovalev, Sergey Priimenko, Natalya V. Ponomareva
2017	—	`conf`	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 Evgeny Tarasov, Dmitry Kovalev
2013	—	`conf`	Декларативная аналитика в мультидиалектной среде (Declarative Analytics in Multidialect Infrastructure). RCDL Dmitry Kovalev