Summer School on Machine Learning: From Data to Mathematical Understanding

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Summer School on Machine Learning: From Data to Mathematical Understanding

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 Apr 30, 2020 

 


WEBPAGE FOR APPLICATIONS:  

http://php.math.unifi.it/users/cime/Courses/2020/course.php?codice=20201
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)
Data pubblicazione
venerdì 28 febbraio 2020 - 14.44.40
Oggetto
Summer School on Machine Learning: From Data to Mathematical Understanding
Pubblicato da
Giandomenico Orlandi
Mathematical methods for applied sciences (seminar course) (2019/2020)
Mathematical modelling in the applied sciences (seminar course) (2019/2020)
Laurea magistrale in Mathematics
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