Efficient tracking of a growing number of experts. - Jaouad Mourtada; Odalric-Ambrym Maillard (ALT, 2017)

Universal consistency and minimax rates for online Mondrian Forests. - Jaouad Mourtada; Stéphane Gaïffas; Erwan Scornet (NIPS, 2017)

Anytime Hedge achieves optimal regret in the stochastic regime. - Jaouad Mourtada; Stéphane Gaïffas (CoRR, 2018)

AMF: Aggregated Mondrian Forests for Online Learning. - Jaouad Mourtada; Stéphane Gaïffas; Erwan Scornet (CoRR, 2019)

On the optimality of the Hedge algorithm in the stochastic regime. - Jaouad Mourtada; Stéphane Gaïffas (J. Mach. Learn. Res., 2019)

Contributions à l'apprentissage statistique : estimation de densité, agrégation d'experts et forêts aléatoires. (Contributions to statistical learning : density estimation, expert aggregation and random forests). - Jaouad Mourtada (2020)

Asymptotics of Ridge(less) Regression under General Source Condition. - Dominic Richards; Jaouad Mourtada; Lorenzo Rosasco (AISTATS, 2021)

Regularized ERM on random subspaces. - Andrea Della Vecchia; Jaouad Mourtada; Ernesto De Vito; Lorenzo Rosasco (AISTATS, 2021)

Distribution-Free Robust Linear Regression. - Jaouad Mourtada; Tomas Vaskevicius; Nikita Zhivotovskiy (CoRR, 2021)

An elementary analysis of ridge regression with random design. - Jaouad Mourtada; Lorenzo Rosasco (CoRR, 2022)

An improper estimator with optimal excess risk in misspecified density estimation and logistic regression. - Jaouad Mourtada; Stéphane Gaïffas (J. Mach. Learn. Res., 2022)

Local Risk Bounds for Statistical Aggregation. - Jaouad Mourtada; Tomas Vaskevicius; Nikita Zhivotovskiy (COLT, 2023)

Universal coding, intrinsic volumes, and metric complexity. - Jaouad Mourtada (CoRR, 2023)

Finite-sample performance of the maximum likelihood estimator in logistic regression. - Hugo Chardon; Matthieu Lerasle; Jaouad Mourtada (CoRR, 2024)

Estimation of discrete distributions in relative entropy, and the deviations of the missing mass. - Jaouad Mourtada (CoRR, 2025)