| 2025 | ICLR | Decentralized Optimization with Coupled Constraints. | Demyan Yarmoshik, Alexander Rogozin, Nikita Kiselev, Daniil Dorin, Alexander V. Gasnikov, Dmitry Kovalev |
| 2025 | ICML | On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms. | Ekaterina Borodich, Alexander V. Gasnikov, Dmitry Kovalev |
| 2025 | UAI | An Optimal Algorithm for Strongly Convex Min-Min Optimization. | Dmitry Kovalev, Alexander V. Gasnikov, Grigory Malinovsky |
| 2023 | ICML | Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks? | Dmitry Metelev, Alexander Rogozin, Dmitry Kovalev, Alexander V. Gasnikov |
| 2022 | AISTATS | An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints. | Adil Salim, Laurent Condat, Dmitry Kovalev, Peter Richtrik |
| 2022 | ICLR | IntSGD: Adaptive Floatless Compression of Stochastic Gradients. | Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtrik |
| 2021 | AISTATS | A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! | Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtrik, Sebastian U. Stich |
| 2021 | ICML | ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. | Dmitry Kovalev, Egor Shulgin, Peter Richtrik, Alexander Rogozin, Alexander V. Gasnikov |
| 2020 | AISTATS | Revisiting Stochastic Extragradient. | Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtrik, Yura Malitsky |
| 2020 | ALT | Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop. | Dmitry Kovalev, Samuel Horvth, Peter Richtrik |
| 2020 | ICML | Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems. | Filip Hanzely, Dmitry Kovalev, Peter Richtrik |
| 2020 | ICML | Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. | Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtrik |
| 2020 | ICML | From Local SGD to Local Fixed-Point Methods for Federated Learning. | Grigory Malinovskiy, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtrik |