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
@@@@@@@@@@@@@@@@@