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Fast kernel methods for data quality monitoring as a goodne..:
Gaia Grosso
;
Nicolò Lai
;
Marco Letizia
...
https://doi.org/10.1088/2632-2153/acebb7. , 2023
Link:
https://doi.org/10.1088/2632-2153/acebb7
RT Journal T1
Fast kernel methods for data quality monitoring as a goodness-of-fit test
UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:f79e57b32c1843a393e4467f9fce9199&Exemplar=1&LAN=DE A1 Gaia Grosso A1 Nicolò Lai A1 Marco Letizia A1 Jacopo Pazzini A1 Marco Rando A1 Lorenzo Rosasco A1 Andrea Wulzer A1 Marco Zanetti PB IOP Publishing YR 2023 K1 machine learning K1 high energy physics K1 data quality K1 monitoring K1 goodness-of-fit K1 Computer engineering. Computer hardware K1 TK7885-7895 K1 Electronic computers. Computer science K1 QA75.5-76.95 JF https://doi.org/10.1088/2632-2153/acebb7 LK http://dx.doi.org/https://doi.org/10.1088/2632-2153/acebb7 DO https://doi.org/10.1088/2632-2153/acebb7 SF ELIB - SuUB Bremen
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