| 2024 | AISTATS | Multitask Online Learning: Listen to the Neighborhood Buzz. | Juliette Achddou, Nicol Cesa-Bianchi, Pierre Laforgue |
| 2024 | AISTATS | Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels. | Tamim El Ahmad, Luc Brogat-Motte, Pierre Laforgue, Florence d'Alch-Buc |
| 2022 | AISTATS | A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits. | Pierre Laforgue, Giulia Clerici, Nicol Cesa-Bianchi, Ran Gilad-Bachrach |
| 2021 | AISTATS | When OT meets MoM: Robust estimation of Wasserstein Distance. | Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alch-Buc |
| 2021 | ICML | Generalization Bounds in the Presence of Outliers: a Median-of-Means Study. | Pierre Laforgue, Guillaume Staerman, Stphan Clmenon |
| 2020 | ICML | Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses. | Pierre Laforgue, Alex Lambert, Luc Brogat-Motte, Florence d'Alch-Buc |
| 2019 | AISTATS | Autoencoding any Data through Kernel Autoencoders. | Pierre Laforgue, Stphan Clmenon, Florence d'Alch-Buc |
| 2019 | ICML | On Medians of (Randomized) Pairwise Means. | Stphan Clmenon, Pierre Laforgue, Patrice Bertail |