| 2025 | ICLR | Optimizing (L0, L1)-Smooth Functions by Gradient Methods. | Daniil Vankov, Anton Rodomanov, Angelia Nedich, Lalitha Sankar, Sebastian U. Stich |
| 2025 | ICML | Exploiting Similarity for Computation and Communication-Efficient Decentralized Optimization. | Yuki Takezawa, Xiaowen Jiang, Anton Rodomanov, Sebastian U. Stich |
| 2025 | ICML | Decoupled SGDA for Games with Intermittent Strategy Communication. | Ali Zindari, Parham Yazdkhasti, Anton Rodomanov, Tatjana Chavdarova, Sebastian U. Stich |
| 2024 | ICML | Non-convex Stochastic Composite Optimization with Polyak Momentum. | Yuan Gao, Anton Rodomanov, Sebastian U. Stich |
| 2024 | ICML | Federated Optimization with Doubly Regularized Drift Correction. | Xiaowen Jiang, Anton Rodomanov, Sebastian U. Stich |
| 2024 | ICML | Universal Gradient Methods for Stochastic Convex Optimization. | Anton Rodomanov, Ali Kavis, Yongtao Wu, Kimon Antonakopoulos, Volkan Cevher |
| 2023 | ICML | Polynomial Preconditioning for Gradient Methods. | Nikita Doikov, Anton Rodomanov |
| 2016 | ICML | A Superlinearly-Convergent Proximal Newton-type Method for the Optimization of Finite Sums. | Anton Rodomanov, Dmitry Kropotov |
| 2014 | ICML | Putting MRFs on a Tensor Train. | Alexander Novikov, Anton Rodomanov, Anton Osokin, Dmitry P. Vetrov |