Abstract
We will address the application of quantum computing to the problem of classification by supervised learning. We will discuss, in particular, the notion of the quantum kernel and its realization and utilization in the context of various machine learning methods. We will also demonstrate the use of a quantum support vector machine on a very topical problem in cybersecurity, namely fraud detection. Our experiments show that quantum kernels promise better performance over classical kernels, although they could not be performed in the ideal scenario of a fault-tolerant universal quantum computer.
About the speaker
Alessandra Di Pierro is an associate professor at the Department of Computer Science - the University of Verona since January 2011. Before then she was a researcher at the Department of Computer Science - the University of Pisa, where she also received her PhD in Computer Science. Alessandra's research interests are in theoretical computer science with the main focus on the theory of quantum computation and its applications to Machine Learning. She is the principal investigator of the QUILAB (Quantum Information Laboratory) research group at the Department of Computer Science in Verona. Since 2017 she is a member of the steering and organising committee of the annual conference QTML (Quantum Techniques in Machine Learning) and field editor for Quantum Software of the Springer journal `Quantum Machine Intelligence.
Participation
Participation is free, but it is mandatory to register online due to Covid-19 restrictions that limit the seats in the room. In compliance with Covid-19 restrictions, access to the room is allowed only with the Digital Covid Certificate (Reinforced Green Pass) and face masks must be worn at all times. Participation is also possible via the Zoom platform, the link will be available soon and will be sent to the registered people.