Sala conferenze IMATI-CNR, Pavia - Tuesday, May 15, 2018 h.15:00
Abstract. Classical approaches to process and classifying data often reduce to designing and minimizing empirical objective functions. The challenge is two-fold. On the one hand, to incorporate the structural information on the problem, on the other hand, to develop optimization schemes that can exploit such a structure. In this talk, I will present an approach based on the forward-backward algorithm both in the context of machine learning and inverse problems. The focus will be on the interplay between estimation and optimization requirements and guarantees.
Università degli Studi di Pavia -
Via Ferrata, 5 - 27100 Pavia
Tel +39.0382.985600 - Fax +39.0382.985602