Machine Learning: From Data to Mathematical Understanding
Levico Terme (Trento) - postponed for covid emerge

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)