| 2025 | ICLR | Universal generalization guarantees for Wasserstein distributionally robust models. | Tam Le, Jrme Malick |
| 2025 | ICML | The Global Convergence Time of Stochastic Gradient Descent in Non-Convex Landscapes: Sharp Estimates via Large Deviations. | Wass Azizian, Franck Iutzeler, Jrme Malick, Panayotis Mertikopoulos |
| 2024 | ICML | What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis. | Wass Azizian, Franck Iutzeler, Jrme Malick, Panayotis Mertikopoulos |
| 2021 | CISS | A Superquantile Approach to Federated Learning with Heterogeneous Devices. | Yassine Laguel, Krishna Pillutla, Jrme Malick, Zad Harchaoui |
| 2021 | COLT | The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities. | Wass Azizian, Franck Iutzeler, Jrme Malick, Panayotis Mertikopoulos |
| 2019 | AISTATS | Model Consistency for Learning with Mirror-Stratifiable Regularizers. | Jalal Fadili, Guillaume Garrigos, Jrme Malick, Gabriel Peyr |
| 2018 | ICML | A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning. | Konstantin Mishchenko, Franck Iutzeler, Jrme Malick, Massih-Reza Amini |
| 2013 | IPCO | Cut-Generating Functions. | Michele Conforti, Grard Cornujols, Aris Daniilidis, Claude Lemarchal, Jrme Malick |
| 2012 | CVPR | Large-scale image classification with trace-norm regularization. | Zad Harchaoui, Matthijs Douze, Mattis Paulin, Miroslav Dudk, Jrme Malick |