| 2025 | ICLR | Sharpness-Aware Minimization: General Analysis and Improved Rates. | Dimitris Oikonomou, Nicolas Loizou |
| 2025 | ICLR | Stochastic Polyak Step-sizes and Momentum: Convergence Guarantees and Practical Performance. | Dimitris Oikonomou, Nicolas Loizou |
| 2024 | AISTATS | Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational Inequalities. | Konstantinos Emmanouilidis, Ren Vidal, Nicolas Loizou |
| 2024 | ICLR | Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates. | Siqi Zhang, Sayantan Choudhury, Sebastian U. Stich, Nicolas Loizou |
| 2023 | AISTATS | Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods. | Aleksandr Beznosikov, Eduard Gorbunov, Hugo Berard, Nicolas Loizou |
| 2023 | ICLR | A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games. | Samuel Sokota, Ryan D'Orazio, J. Zico Kolter, Nicolas Loizou, Marc Lanctot, Ioannis Mitliagkas, Noam Brown, Christian Kroer |
| 2022 | AISTATS | Stochastic Extragradient: General Analysis and Improved Rates. | Eduard Gorbunov, Hugo Berard, Gauthier Gidel, Nicolas Loizou |
| 2022 | AISTATS | Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity. | Eduard Gorbunov, Nicolas Loizou, Gauthier Gidel |
| 2022 | AISTATS | On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging. | Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan |
| 2021 | AISTATS | SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation. | Robert M. Gower, Othmane Sebbouh, Nicolas Loizou |
| 2021 | AISTATS | Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. | Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien |
| 2020 | ICML | A Unified Theory of Decentralized SGD with Changing Topology and Local Updates. | Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian U. Stich |
| 2020 | ICML | Stochastic Hamiltonian Gradient Methods for Smooth Games. | Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas |
| 2019 | ICASSP | Provably Accelerated Randomized Gossip Algorithms. | Nicolas Loizou, Michael G. Rabbat, Peter Richtrik |
| 2019 | ICML | Stochastic Gradient Push for Distributed Deep Learning. | Mahmoud Assran, Nicolas Loizou, Nicolas Ballas, Michael G. Rabbat |
| 2019 | ICML | SGD with Arbitrary Sampling: General Analysis and Improved Rates. | Xun Qian, Peter Richtrik, Robert M. Gower, Alibek Sailanbayev, Nicolas Loizou, Egor Shulgin |
| 2016 | ICORES | Distributionally Robust Games with Risk-averse Players. | Nicolas Loizou |