Dmitry Kovalev

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 63

Top Topics

Gradient Method

Convex Optimization

Top Venues

Publications

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) (2024)
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 (2024)
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) (2024)
Dmitry Metelev, Alexander Rogozin, Dmitry Kovalev, Alexander V. Gasnikov
Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks? ICML (2023)
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) (2023)
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) (2023)
Dmitry Kovalev, Alexander V. Gasnikov, Grigory Malinovsky
An Optimal Algorithm for Strongly Convex Min-min Optimization. CoRR (2022)
Dmitry Kovalev, Alexander V. Gasnikov
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization. CoRR (2022)
Dmitry Kovalev, Alexander V. Gasnikov
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization. NeurIPS (2022)
Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtárik
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with Inexact Prox. CoRR (2022)
Aleksandr Beznosikov, Aibek Alanov, Dmitry Kovalev, Martin Takác, Alexander V. Gasnikov
On Scaled Methods for Saddle Point Problems. CoRR (2022)
Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich, Alexander V. Gasnikov, Gesualdo Scutari
Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity. CoRR (2022)
Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtárik
IntSGD: Adaptive Floatless Compression of Stochastic Gradients. ICLR (2022)
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)
Aleksandr Beznosikov, Boris Polyak, Eduard Gorbunov, Dmitry Kovalev, Alexander V. Gasnikov
Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems - Survey. CoRR (2022)
Dmitry Kovalev, Alexander V. Gasnikov
The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization. CoRR (2022)
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)
Adil Salim, Laurent Condat, Dmitry Kovalev, Peter Richtárik
An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints. AISTATS (2022)
Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtárik
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox. NeurIPS (2022)
Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov
Optimal Algorithms for Decentralized Stochastic Variational Inequalities. NeurIPS (2022)
Evgenia Romanenkova, Alina Rogulina, Anuar Shakirov, Nikolay Stulov, Alexey Zaytsev, Leyla S. Ismailova, Dmitry Kovalev, Klemens Katterbauer, Abdallah AlShehri
Similarity learning for wells based on logging data. CoRR (2022)
Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov
Optimal Algorithms for Decentralized Stochastic Variational Inequalities. CoRR (2022)
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 (2022)
Dmitry Kovalev, Alexander V. Gasnikov
The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization. NeurIPS (2022)
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)
Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtárik
IntSGD: Floatless Compression of Stochastic Gradients. CoRR (2021)
Alexander Rogozin, Vladislav Lukoshkin, Alexander V. Gasnikov, Dmitry Kovalev, Egor Shulgin
Towards Accelerated Rates for Distributed Optimization over Time-Varying Networks. OPTIMA (2021)
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)
Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander V. Gasnikov
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. CoRR (2021)
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 (2021)
Dmitry Kovalev, Alexander V. Gasnikov, Peter Richtárik
Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling. CoRR (2021)
Alexander Rogozin, Aleksandr Beznosikov, Darina Dvinskikh, Dmitry Kovalev, Pavel E. Dvurechensky, Alexander V. Gasnikov
Decentralized Distributed Optimization for Saddle Point Problems. CoRR (2021)
Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander V. Gasnikov
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. ICML (2021)
Aleksandr Beznosikov, Alexander Rogozin, Dmitry Kovalev, Alexander V. Gasnikov
Near-Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks. OPTIMA (2021)
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)
Grigory Malinovsky, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtárik
From Local SGD to Local Fixed Point Methods for Federated Learning. CoRR (2020)
Filip Hanzely, Dmitry Kovalev, Peter Richtárik
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems. CoRR (2020)
Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. ICML (2020)
Dmitry Kovalev, Robert M. Gower, Peter Richtárik, Alexander Rogozin
Fast Linear Convergence of Randomized BFGS. CoRR (2020)
Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtárik, Sebastian U. Stich
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! CoRR (2020)
Eduard A. Gorbunov, Dmitry Kovalev, Dmitry Makarenko, Peter Richtárik
Linearly Converging Error Compensated SGD. CoRR (2020)
Grigory Malinovskiy, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtárik
From Local SGD to Local Fixed-Point Methods for Federated Learning. ICML (2020)
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)
Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. CoRR (2020)
Filip Hanzely, Dmitry Kovalev, Peter Richtárik
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems. ICML (2020)
Dmitry Kovalev, Adil Salim, Peter Richtárik
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization. NeurIPS (2020)
Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky
Revisiting Stochastic Extragradient. AISTATS (2020)
Eduard A. Gorbunov, Dmitry Kovalev, Dmitry Makarenko, Peter Richtárik
Linearly Converging Error Compensated SGD. NeurIPS (2020)
Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky
Revisiting Stochastic Extragradient. CoRR (2019)
Dmitry Kovalev, Konstantin Mishchenko, Peter Richtárik
Stochastic Newton and Cubic Newton Methods with Simple Local Linear-Quadratic Rates. CoRR (2019)
Dmitry Kovalev, Samuel Horvath, Peter Richtárik
Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop. CoRR (2019)
Sélim Chraibi, Ahmed Khaled, Dmitry Kovalev, Peter Richtárik, Adil Salim, Martin Takác
Distributed Fixed Point Methods with Compressed Iterates. CoRR (2019)
Adil Salim, Dmitry Kovalev, Peter Richtárik
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates. NeurIPS (2019)
Adil Salim, Dmitry Kovalev, Peter Richtárik
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates. CoRR (2019)
Robert M. Gower, Dmitry Kovalev, Felix Lieder, Peter Richtárik
RSN: Randomized Subspace Newton. NeurIPS (2019)
Dmitry Kovalev, Peter Richtárik, Eduard A. Gorbunov, Elnur Gasanov
Stochastic Spectral and Conjugate Descent Methods. NeurIPS (2018)
Dmitry Kovalev, Leonid A. Kalinichenko, Sergey A. Stupnikov
Organization of Virtual Experiments in Data-Intensive Domains: Hypotheses and Workflow Specification. DAMDID/RCDL (2017)
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)
Dmitry Kovalev, Sergey Priimenko, Natalya Ponomareva
Search for Gender Difference in Functional Connectivity of Resting State fMRI. DAMDID/RCDL (2017)
Nikolay A. Skvortsov, Leonid A. Kalinichenko, Dmitry Kovalev
Концептуальное моделирование предметных областей с интенсивным использованием данных (Conceptual modeling of subject domains in data intensive research). DAMDID/RCDL (2016)
Igor Kovalev, Pavel Zelenkov, Margarita Karaseva, Dmitry Kovalev
Ant Algorithm Modification for Multi-Version Software Building. ICSI (1) (2015)
Stanislav Philippov, Victor N. Zakharov, Sergey A. Stupnikov, Dmitry Kovalev
Подходы к повышению пертинентности информационного предложения в медиасервисах на основе обработки больших объемов данных (Approaches to Improve the Pertinence of Information in the Media Services on the Basis of BigData Processing). DAMDID/RCDL (2015)
Stanislav Philippov, Victor N. Zakharov, Sergey A. Stupnikov, Dmitry Kovalev
Организация больших объемов данных в рекомендательных системах поддержки жизнеобеспечения, входящих в состав глобальных платформ электронной коммерции (Organization of Big Data in the Global E-commerce Platforms). DAMDID/RCDL (2015)
Leonid A. Kalinichenko, Sergey A. Stupnikov, Alexey Vovchenko, Dmitry Kovalev
Multi-dialect Workflows. ADBIS (2014)
Leonid A. Kalinichenko, Dmitry Kovalev, Dana Kovaleva, Oleg Malkov
Введение в анализ методов и средств поддержки научных экспериментов, движимых гипотезами (Introduction into Analysis of Methods and Tools for Hypothesis-Driven Scientific Experiment Support). RCDL (2014)
Alexey Vovchenko, Leonid A. Kalinichenko, Dmitry Kovalev
Программирование методов разрешения сущностей и слияния данных при реализации ETL в среде Hadoop (Programming of the Entity Resolution and Data Fusion Methods While Implementing ETL in the Hadoop Environment). RCDL (2014)
Nikolay A. Skvortsov, Dmitry O. Briukhov, Leonid A. Kalinichenko, Dmitry Kovalev, Sergey A. Stupnikov
Метаданные о научных методах для обеспечения их повторного использования и воспроизводимости результатов (Scientific Methods Metadata for Provision of the Methods Reuse and Result Reproducibility). RCDL (2013)
Dmitry Kovalev
Декларативная аналитика в мультидиалектной среде (Declarative Analytics in Multidialect Infrastructure). RCDL (2013)
Leonid A. Kalinichenko, Sergey A. Stupnikov, Alexey Vovchenko, Dmitry Kovalev
Rule-Based Multi-dialect Infrastructure for Conceptual Problem Solving over Heterogeneous Distributed Information Resources. ADBIS (2) (2013)