3 papers
stat.ML2026
Topological Exploration of High-Dimensional Empirical Risk Landscapes: general approach, and applications to phase retrieval
Antoine Maillard, Tony Bonnaire, Giulio Biroli
We consider the landscape of empirical risk minimization for high-dimensional Gaussian single-index models (generalized linear models). The objective is to recover an unknown signa…
cs.LG2025
Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training
Tony Bonnaire, Raphaël Urfin, Giulio Biroli +1
Diffusion models have achieved remarkable success across a wide range of generative tasks. A key challenge is understanding the mechanisms that prevent their memorization of traini…
cs.LG2025
The Role of the Time-Dependent Hessian in High-Dimensional Optimization
Tony Bonnaire, Giulio Biroli, Chiara Cammarota
Gradient descent is commonly used to find minima in rough landscapes, particularly in recent machine learning applications. However, a theoretical understanding of why good solutio…