Jaouad Mourtada

About me

I am a PhD student in statistics and machine learning in the Center for Applied Mathematics (CMAP) at École Polytechnique, under the supervision of Stéphane Gaïffas and Erwan Scornet.

I am broadly interested in statistics and learning theory, and more specifically in online learning, Random forest methods and density estimation.


  • Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet. AMF: Aggregated Mondrian forests for online learning. ArXiv preprint, 2019. [PDF] [arXiv]

  • Jaouad Mourtada, Stéphane Gaïffas. On the optimality of the Hedge algorithm in the stochastic regime. Journal of Machine Learning Research, 20(83):1−28, 2019. [PDF] [Link] [arXiv] [Slides] [Bibtex]

  • Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet. Minimax optimal rates for Mondrian trees and forests. To appear in Annals of Statistics, 2019+. [PDF] [arXiv] [Bibtex]

  • Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet. Universal consistency and minimax rates for online Mondrian Forests. In Advances in Neural Information and Processing Systems (NeurIPS), 2017. [PDF] [Link] [arXiv] [Poster] [Bibtex]

  • Jaouad Mourtada, Odalric-ambrym Maillard. Efficient tracking of a growing number of experts. In Proceedings of the 28th international conference on Algorithmic Learning Theory (ALT), 2017. [PDF] [Link] [arXiv] [Slides] [Bibtex]


Reviewer for NeurIPS 2018, 2019 and ICML 2019.


Email: jaouad (dot) mourtada (at) polytechnique (dot) edu

Office: Room 2011 (second floor) in the CMAP Lab at École Polytechnique  —  91128 Palaiseau, France