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SUMMARY:Machine learning at LHCb
DTSTART;VALUE=DATE-TIME:20181023T134500Z
DTEND;VALUE=DATE-TIME:20181023T140500Z
DTSTAMP;VALUE=DATE-TIME:20260421T235210Z
UID:indico-contribution-1301@cern.ch
DESCRIPTION:Speakers: Nikita Kazeev (Higher School of Economics\, Yandex S
 chool of Data Analysis)\nMachine learning methods are widely used in the L
 HCb experiment at every stage of data processing. This talk will cover som
 e of the established applications of machine learning\, such as the classi
 fication and selection of interesting events in triggering and offline ana
 lysis of the data\, such as particle identification\, unbiased offline cha
 racterization of reconstructed events\, tracking\, and data quality assess
 ment. We will also discuss ongoing and future developments\, including  ch
 allenges of dealing with the luminosity increase and the migration to a pu
 re software trigger\, which is planned for LHC Run III\, as well as the ap
 plication of Generative Adversarial Networks to fast detector simulation.\
 n\nhttps://indico.particle.mephi.ru/event/22/contributions/1301/
LOCATION:Hotel Intourist Kolomenskoye 4* Alekseevskiy hall
URL:https://indico.particle.mephi.ru/event/22/contributions/1301/
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