Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization. - Gaspard Beugnot; Julien Mairal; Alessandro Rudi (NeurIPS, 2021)

Improving approximate optimal transport distances using quantization. - Gaspard Beugnot; Aude Genevay; Kristjan H. Greenewald; Justin Solomon 001 (UAI, 2021)

On the Benefits of Large Learning Rates for Kernel Methods. - Gaspard Beugnot; Julien Mairal; Alessandro Rudi (COLT, 2022)

GloptiNets: Scalable Non-Convex Optimization with Certificates. - Gaspard Beugnot; Julien Mairal; Alessandro Rudi (NeurIPS, 2023)

Optimization, Generalization and Non-convex Optimization With Kernel Methods. (Optimisation, Généralisation et optimisation non convexe avec les méthodes à noyaux). - Gaspard Beugnot (2024)