Dear all, As part of the CN1-SPOKE 10 on Quantum Computing, we are organizing a weekly seminar series. Next week’s seminar is: Title: Statistical Complexity of Quantum Learning Speaker: Leonardo Banchi (Università degli Studi di Firenze) Venue: Room 250, Ed. C, Polo Fibonacci (Physics Department, first floor) Time: Monday, 08/04/2024, 17:00 Abstract: Recent years have seen significant activity on the problem of using data for the purpose of learning properties of quantum systems or of processing classical or quantum data via quantum computing. As in classical learning, quantum learning problems involve settings in which the mechanism generating the data is unknown, and the main goal of a learning algorithm is to ensure satisfactory accuracy levels when only given access to data and, possibly, side information such as expert knowledge. I will introduce the complexity of quantum learning using information-theoretic techniques by focusing on data complexity, copy complexity, and model complexity. Copy complexity arises from the destructive nature of quantum measurements, which irreversibly alter the state to be processed, limiting the information that can be extracted about quantum data. For example, in a quantum system, unlike in classical machine learning, it is generally not possible to evaluate the training loss simultaneously on multiple hypotheses using the same quantum data. To make the seminar approachable by different research communities, I will provide extensive background material on classical results from statistical learning theory, as well as on the distinguishability of quantum states. Throughout, we highlight the differences between quantum and classical learning by addressing both supervised and unsupervised learning, and discuss potential advantages. Reference: arXiv:2309.11617 - Adv. Quant. Tech 2024 - in press Everyone is welcome! @@@@@@@@@@@@@@@@@ Gianna M. Del Corso, PhD Dipartimento di Informatica, Università di Pisa Largo Pontecorvo, 3 56127 Pisa, Italy ph. +39-050-2213118 @@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@ Gianna M. Del Corso, PhD Dipartimento di Informatica, Università di Pisa Largo Pontecorvo, 3 56127 Pisa, Italy ph. +39-050-2213118 @@@@@@@@@@@@@@@@@