Machine Learning: From Data to Mathematical Understanding

Please, keep in account that the below information must be confirmed, basing on the epidemic situation.

CIME-CIRM- EMS Summer School in Applied Mathematics

Course directors:

C. Agostinelli (Univ. Trento, Italy)
  claudio.agostinelli@unitn.it
M. Fornasier (Technical Univ. Munich, Germany )
  massimo.fornasier@ma.tum.de
L. Rosasco (Univ. Genova- IIT, Italy - MIT, U.S.A.)
  Lorenzo.Rosasco@unige.it
R. Willett (Univ. Chicago, U.S.A.)
  willett@uchicago.edu

You can apply
from Dec 1, 2019
to Mar 23, 2020

Lectures:

P. Rigollet MIT, USA	Statistical Optimal Transport

L. Rosasco Univ. Genova- IIT, Italy - MIT, U.S.A.	Regularization Approaches to Machine Learning

C. Schoenlieb Univ. Cambridge, U.K.	Mathematical imaging and Machine Learning

J. Tropp California Institute of Technology - USA	Randomized algorithms for linear algebra

S. Wright Univ. Wisconsin, USA	Fundamental Optimization Algorithms for Data Science

CIME activity is carried out with the collaboration and financial support of:
- INdAM (Istituto Nazionale di Alta Matematica)