| 2025 | AISTATS | Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation. | Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines |
| 2025 | ICML | Unified Breakdown Analysis for Byzantine Robust Gossip. | Renaud Gaucher, Aymeric Dieuleveut, Hadrien Hendrikx |
| 2025 | ICML | Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up. | Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Eric Moulines |
| 2024 | AISTATS | Proving Linear Mode Connectivity of Neural Networks via Optimal Transport. | Damien Ferbach, Baptiste Goujaud, Gauthier Gidel, Aymeric Dieuleveut |
| 2024 | AISTATS | Compression with Exact Error Distribution for Federated Learning. | Mahmoud Hegazy, Rmi Leluc, Cheuk Ting Li, Aymeric Dieuleveut |
| 2024 | ICML | Random features models: a way to study the success of naive imputation. | Alexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet |
| 2024 | ICML | Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates. | Rmi Leluc, Aymeric Dieuleveut, Franois Portier, Johan Segers, Aigerim Zhuman |
| 2023 | ICML | Naive imputation implicitly regularizes high-dimensional linear models. | Alexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet |
| 2023 | ICML | Conformal Prediction with Missing Values. | Margaux Zaffran, Aymeric Dieuleveut, Julie Josse, Yaniv Romano |
| 2022 | AISTATS | Super-Acceleration with Cyclical Step-sizes. | Baptiste Goujaud, Damien Scieur, Aymeric Dieuleveut, Adrien B. Taylor, Fabian Pedregosa |
| 2022 | AISTATS | Differentially Private Federated Learning on Heterogeneous Data. | Maxence Noble, Aurlien Bellet, Aymeric Dieuleveut |
| 2022 | AISTATS | QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning. | Maxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines |
| 2022 | ICML | Near-optimal rate of consistency for linear models with missing values. | Alexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet |
| 2022 | ICML | Adaptive Conformal Predictions for Time Series. | Margaux Zaffran, Olivier Fron, Yannig Goude, Julie Josse, Aymeric Dieuleveut |
| 2020 | AISTATS | Context Mover's Distance & Barycenters: Optimal Transport of Contexts for Building Representations. | Sidak Pal Singh, Andreas Hug, Aymeric Dieuleveut, Martin Jaggi |
| 2020 | ICML | On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent. | Scott Pesme, Aymeric Dieuleveut, Nicolas Flammarion |
| 2019 | ICLR | Context Mover's Distance & Barycenters: Optimal transport of contexts for building representations. | Sidak Pal Singh, Andreas Hug, Aymeric Dieuleveut, Martin Jaggi |