Dipartimento di Matematica "Giuseppe Peano"

Lezione lagrangiana

The mathematics of Machine Learning

Relatore:
Lorenzo Rosasco,
Universitá di Genova 

Data e luogo:
26 ottobre 2023 dalle 14.30 alle 15.30
in Aula De Filippi, Via Accademia Albertina 13, presso DBIOS, Torino

Abstract 
In this talk, I will provide a self contained introduction to the main mathematical
framework of machine learning, namely statistical learning theory. I will also describe
some of the key results and current challenges in the field.

Short Bio
Professor Lorenzo Rosasco is full professor in Computer Science Department of Computer Science, Bioengineering, Robotics and Systems Engineering. He also holds a research scientist at MIT and a collaborator position at the Istituto Italiano di Tecnologia.
Prof Rosasco received his PhD from the University of Genova in 2006 where he worked under the supervision of Alessandro Verri and Ernesto De Vito in the SLIPGURU. He was a visiting student with Tomaso Poggio at the Center for Biological and Computational Learning (CBCL) at MIT, and with Steve Smale at the Toyota Technological Institute at Chicago (TTI-Chicago.) Between 2006 and 2009 he was a postdoctoral fellow at CBCL working with Tomaso Poggio.
In 2019 he won a European Research Council (ERC consolidator) grant with the project "Efficient algorithms for sustainable machine learning". The grant is funded with €2 million over 5 years, and is part of the Horizon 2020 European research and development program.
Prof Rosasco's research focuses on studying theory and algorithms for machine learning. Prof Rosasco has developed and analyzed methods to learn from small as well as large samples of high dimensional data, using analytical and probabilistic tools, within a multidisciplinary approach drawing concepts and techniques primarily from computer science but also from statistics, engineering and applied mathematics.