3 papers
math.OC2026
On the global convergence of gradient flow for wide shallow models beyond homogeneous nonlinearities
Romain Petit, Clarice Poon, Gabriel Peyré +1
A surprising phenomenon in the training of neural networks is the ability of gradient descent to find global minimizers of the training loss despite its non-convexity. Following ea…
math.NA2025
On the non-convexity issue in the radial Calderón problem
Giovanni S. Alberti, Romain Petit, Clarice Poon +1
A classical approach to the Calderón problem is to estimate the unknown conductivity by solving a nonlinear least-squares problem. It leads to a nonconvex optimization problem whi…
math.AP2025
A convex lifting approach for the Calderón problem
Giovanni S. Alberti, Romain Petit, Simone Sanna
The Calderón problem consists in recovering an unknown coefficient of a partial differential equation from boundary measurements of its solution. These measurements give rise to a…