Guillaume Garrigos

My research essentially focuses on dynamical systems associated to optimization problems. In particular, I am interested in algorithms and regularization methods for nonsmooth (eventually nonconvex) problems arising in signal/image processing and machine learning. I am particularly interested in the interplay between the modelization of a learning/inverse problem as an optimization problem, and its resolution. My papers are here.

I am a CNRS postdoc researcher at the École Normale Supérieure (DMA), member of the NORIA (Numerical Optimal tRansport for ImAging) research group.

Formerly, I used to be a postdoc researcher at the Laboratory for Computational and Statistical Learning, a joint lab between the IIT and MIT. Before that I did a PhD in Optimization between the Université de Montpellier and the Universidad Santa Maria.