| 2025 | ICLR | MAST: model-agnostic sparsified training. | Yury Demidovich, Grigory Malinovsky, Egor Shulgin, Peter Richtrik |
| 2025 | ICLR | Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization. | Yury Demidovich, Petr Ostroukhov, Grigory Malinovsky, Samuel Horvth, Martin Takc, Peter Richtrik, Eduard Gorbunov |
| 2025 | UAI | An Optimal Algorithm for Strongly Convex Min-Min Optimization. | Dmitry Kovalev, Alexander V. Gasnikov, Grigory Malinovsky |
| 2024 | AAAI | Minibatch Stochastic Three Points Method for Unconstrained Smooth Minimization. | Soumia Boucherouite, Grigory Malinovsky, Peter Richtrik, El Houcine Bergou |
| 2023 | AISTATS | Can 5th Generation Local Training Methods Support Client Sampling? Yes! | Michal Grudzien, Grigory Malinovsky, Peter Richtrik |
| 2023 | UAI | Random Reshuffling with Variance Reduction: New Analysis and Better Rates. | Grigory Malinovsky, Alibek Sailanbayev, Peter Richtrik |
| 2022 | ICML | ProxSkip: Yes! Local Gradient Steps Provably Lead to Communication Acceleration! Finally! | Konstantin Mishchenko, Grigory Malinovsky, Sebastian U. Stich, Peter Richtrik |