Relatore:
Davide Pastorello
- Alma Mater Studiorum, Università di Bologna, Department of Mathematics
lunedì 27 maggio 2024
alle ore
14.00
Aula I
Abstract:
The application of quantum computing to machine learning offers some interesting solutions characterized by a quantum advantage with respect to the classical counterparts in terms of time and space complexity, expressive power, generalization capability, at least on a theoretical level. In this lecture, we give an overview on some quantum machine learning algorithms including distance-based classifiers and different kinds of quantum neural networks. In particular, we focus on the most promising approaches relating to existing and near-term quantum machines.
Short cv:
Davide Pastorello received the M.Sc. degrees in Physics and the Ph.D. degree in Mathematics from the University of Trento in 2011 and 2014, respectively. From 2015 to 2019 he was postdoc researcher at Deptartment of Mathematics, University of Trento, also with a 2-year grant from Fondazione Caritro as P.I. of a project on quantum computing. From 2020 to 2023 he was Assistant Professor at the Department of Information Engineering and Computer Science (DISI), University of Trento. Since 2023, he is Assistant Professor at Deptartment of Mathematics, University of Bologna. His main research interests are: mathematical foundations of quantum mechanics, mathematical methods in quantum computing and quantum machine learning.
