Since July 1st, I am a researcher (‘chargé de recherche‘) at Inria Lyon and Université Jean Monnet, in the Malice team, located in Laboratoire Hubert Curien. I work on optimization, games, and representation learning.

From November 2021 to June 2024, I was a post-doctoral researcher at Mila working with Gauthier Gidel and Simon Lacoste-Julien. Prior to this position, I did my Ph. D. at Inria Paris-Saclay (in the Parietal Team) under the supervision of Joseph Salmon and Alexandre Gramfort. I worked on the optimization and statistical aspects of high dimensional sparse linear regression applied to brain signal reconstruction.

In particular,

• Our recent works on self-consuming generative models and their biases got media coverage from the N.Y. times!

• I developed Python packages for fast computation and automatic hyperparameter selection of sparse linear models.

Here is a short resume and my list of publications.

Contact

News

• 09-29-2024 I was delighted to be a keynote speaker for the ECCV workshop ¨The Dark Side of Generative AIs and Beyond¨, here are the slides

• 09-26-2024 Our paper showing that Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences was just accepted to NeurIPS! See you in Vancouver!

• 08-26-2024 Our recent works on self-consuming generative models and their biases was featured in the N.Y. times!

• 07-01-2024 Just started as an Inria researcher in the Malice team

• 04-22-2024 The recording of the talk On the Stability of Iterative Retraining of Generative Models on their own Data at the Montreal Machine Learning Seminar can be found here

• 01-16-2024 Our paper On the Stability of Iterative Retraining of Generative Models on their own Data was accepted to ICLR 2024 with a spotlight, see you in Vienna!

• 12-18-2023 We just released our paper proving that Q-learners can provably learn to collude in the iterated prisoner dilemma!

• 01-07-2023 On July 1st, 2024 I will join Inria as a Research Scientist!

Previous News

• 05-12-2023 I will present our paper On the Limitations of Elo: Real-World Games are Transitive, not Additive at the Berkeley Multi-Agent Reinforcement Learning Seminar

• Our paper Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning has been accepted at ICML 2023, see you in Hawaii!

• Our paper On the Limitations of Elo: Real-World Games are Transitive, not Additive has been accepted to AISTATS 2023, see you in Spain!

• I just presented our paper Synergies between Disentanglement and Sparsity: a Multi-task Learning Perspective at the Canadian Mathematical Society Winter Workshop

• I just presented our two papers Beyond L1: Faster and Better Sparse Models with skglm and The Curse of Unrolling: Rate of Differentiating Through Optimization at NeurIPS 2022

• I was awarded the top reviewer award at NeurIPS 2022!

• Our papers Beyond L1: Faster and Better Sparse Models with skglm and The Curse of Unrolling: Rate of Differentiating Through Optimization have been accepted to NeurIPS 2022!