This introductory school, as well as the associated workshop
that will be held in 2022, is organized within the framework of the Dipartimento di Eccellenza "Classe di Scienze” of the Scuola Normale Superiore.
The spirit of these two activities is related to that of the school: Mathematical and Computational Aspects of Machine Learning organized at Centro De Giorgi in October 2019.
The plan of both the school and the workshop is to bring together Machine Learning researchers working on theoretical questions at the interface between Mathematics and Computer science.
The speakers will introduce the mathematical foundations of Machine Learning, discuss the current state of the art, but also highlight future research directions and open problems.
The lectures will target a broad audience of early stage mathematicians (Ph.D and advanced Master level).
In particular, the introductory week will focus on master level courses introducing the mathematical basis of machine learning.
The prerequisites will be master level courses in probability, calculus and linear algebra.
The boot-camp week, as well as the workshop, is to focus on the following topics:
1) Statistical Learning Theory and Regularization (L. Rosasco)
2) Mathematics of Neural Networks (L. Chizat and A. Montanari)
3) Optimization for Machine Learning (S. Villa)
4) Optimal Transport and Machine Learning (S. Di Marino, A. Gerolin and P. Rigollet)
5) Applications in Medical Sciences (Jean-Philippe Vert)
In principle, the School will take place at the Centro De Giorgi and the number of participants will be constrained to the capacity limit for this type of event.
The deadline for application is 1st December 2021. For the application procedure, please go to Registration
The confirmation of admission for the school will be communicated to registered participants in the first half of December.
The workshop will take place in hybrid mode, with a maximum of 50 persons in presence. Upon reaching this maximum limit, registration will close automatically. In the event of impediments due to new covid-19 pandemic measures, the school will run completely from remote on the same dates.
Online participation requires registration as well. If you plan on attending online, send an email to the address: firstname.lastname@example.org