Journal papers
- Concentration study of M-estimators using the influence function, in Electronic Journal of Statistics (2022) (project euclid).
- Excess risk bounds in robust empirical risk minimization, with S. Minsker, (2020), in Information and Inference: A Journal of the IMA (arxiv).
- Robust classification via MOM minimization, with M. Lerasle and G. Lecué, (2020), published in Machine Learning (arxiv).
- Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic Algorithm, with O. Maillard and D. Basu, (2022), to appear in TMLR (arxiv).
Conference papers
- MONK – Outlier-Robust Mean Embedding Estimation by Median-of-Means, with Matthieu Lerasle, Zoltan Szabo, and Guillaume Lecué, (2019) in ICML (pmlr, arxiv).
- Topics in robust statistical learning, with Claire Brécheteau, Edouard Genetay and Adrien Saumard, published in ESAIM: PROCEEDINGS AND SURVEYS (HAL).
- CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption, with S. Agrawal, O. Maillard and D. Basu, (2024) in ALT, (arxiv).
Pre-prints
- AdaStop: sequential testing for efficient and reliable comparisons of Deep RL Agents, with Riccardo Della Vecchia, Alena Shilova, Matheus Centa de Medeiros, Hector Kohler, Odalric-Ambrym Maillard, Philippe Preux (2023), (arxiv).
- Information Lower Bounds for Robust Mean Estimation, with Rémy Degenne (2024) (arxiv).
PhD
M-estimation and Median of Means applied to statistical learning, Ph.D. dissertation (2021) (HAL).