Grosso, Gaia https://orcid.org/0000-0002-8303-3291
Lai, Nicolò https://orcid.org/0000-0001-9973-6509
Letizia, Marco https://orcid.org/0000-0001-9641-4352
Pazzini, Jacopo https://orcid.org/0000-0002-1118-6205
Rando, Marco https://orcid.org/0009-0008-3839-1429
Rosasco, Lorenzo https://orcid.org/0000-0003-3098-383X
Wulzer, Andrea https://orcid.org/0000-0002-4523-1940
Zanetti, Marco https://orcid.org/0000-0003-4281-4582
Funding for this research was provided by:
Air Force Office of Scientific Research (BAA-AFRL-AFOSR-2016-0007)
Division of Computing and Communication Foundations (CCF-1231216)
H2020 Marie Skłodowska-Curie Actions (NoMADS - DLV-777826)
H2020 European Research Council (772369)
Agencia Estatal de Investigación (PID2020-115845GB-I00/AEI/10.13039/501100011033)
Article Title: Fast kernel methods for data quality monitoring as a goodness-of-fit test
Journal Title: Machine Learning: Science and Technology
Article Type: paper
Copyright Information: © 2023 The Author(s). Published by IOP Publishing Ltd
Publication dates
Date Received: 2023-03-30
Date Accepted: 2023-07-28
Online publication date: 2023-08-25