I am a PhD student in applied mathematics in Grenoble. I have the honour of having the amazing trio Franck Iutzeler, Jérôme Malick and Panayotis Mertikopoulos as adviors. More precisely, I am at the LJK lab, which is part of UGA.
I am in charge of the team’s seminar, please get in touch if you would like to present!
My current interest are robust optimization, non-convex stochastic optimization and online learning.
Inspired by the success of entropic regularization in optimal transport, we study the regularization of WDRO (ESAIM COCV). We also show that these estimators enjoy attractive generalization guarantees (NeurIPS 23).
We characterize the last iterate convergence rate of mirror methods in variational inequalities as a function of the local geometry of the Bregman divergence near the solution, both in the deterministic (under review) and stochastic settings (COLT 21).
With Marc Lelarge, we precisely describe the approximatyion cabapilities of invariant and equivariant graph neural networks (ICLR 21). It was presented at a MIPT-UGA workshop and at the Thoth team seminar (slides).
With Gauthier Gidel, Ioannis Mitliagkas and Simon Lacoste-Julien, we propose a tight and unified analysis of gradient-based methods in games (AISTATS 20, slides) and leverage matrix iteration theory to study accelerated methods in games (AISTATS 20).