The Mathematics of Machine Learning

Co-founded by PRIN: Gradient flows, Optimal Transport and Metric Measure Structures, AFORS, CRCNSERC: Artificial Intelligence at the Interface of Chemistry and Mathematics

16 January 2023 - 20 January 2023

Aims

The introductory school and associated workshop are organized following previous activities within the framework of the Dipartimenti di Eccellenza "Classe di Scienze”.

The spirit of these activities are related to that of the school: Mathematical and Computational Aspects of Machine Learning workshop 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 will focus on the following topics:
- Statistical Learning Theory and Regularization (E. De Vito e S. Salzo)
- Optimization for Machine Learning (S. Villa)
- Optimal Transport and Machine Learning (S. Di Marino, A. Gerolin)
ATTENTION: The School will be held only in person.

VIDEO: a playlist of the talks is available on Youtube.