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Advanced Machine Learning for Classification, Regression, and Generation in Jet Physics

<!--HTML--><p>There is a deep connection between machine learning and jet physics - after all, jets are defined by unsupervised learning algorithms. Jet physics has been a driving force for studying modern machine learning in high energy physics. Domain specific challenges require new te...

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Autor principal: Nachman, Ben
Lenguaje:eng
Publicado: 2017
Materias:
Acceso en línea:http://cds.cern.ch/record/2292926
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author Nachman, Ben
author_facet Nachman, Ben
author_sort Nachman, Ben
collection CERN
description <!--HTML--><p>There is a deep connection between machine learning and jet physics - after all, jets are defined by unsupervised learning algorithms. Jet physics has been a driving force for studying modern machine learning in high energy physics. Domain specific challenges require new techniques to make full use of the algorithms. A key focus is on understanding how and what the algorithms learn. Modern machine learning techniques for jet physics are demonstrated for classification, regression, and generation. In addition to providing powerful baseline performance, we show how to train complex models directly on data and to generate sparse stacked images with non-uniform granularity.</p>
id cern-2292926
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2017
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spelling cern-22929262022-11-02T22:31:44Zhttp://cds.cern.ch/record/2292926engNachman, BenAdvanced Machine Learning for Classification, Regression, and Generation in Jet PhysicsAdvanced Machine Learning for Classification, Regression, and Generation in Jet PhysicsEP-IT Data science seminars<!--HTML--><p>There is a deep connection between machine learning and jet physics - after all, jets are defined by unsupervised learning algorithms. Jet physics has been a driving force for studying modern machine learning in high energy physics. Domain specific challenges require new techniques to make full use of the algorithms. A key focus is on understanding how and what the algorithms learn. Modern machine learning techniques for jet physics are demonstrated for classification, regression, and generation. In addition to providing powerful baseline performance, we show how to train complex models directly on data and to generate sparse stacked images with non-uniform granularity.</p>oai:cds.cern.ch:22929262017
spellingShingle EP-IT Data science seminars
Nachman, Ben
Advanced Machine Learning for Classification, Regression, and Generation in Jet Physics
title Advanced Machine Learning for Classification, Regression, and Generation in Jet Physics
title_full Advanced Machine Learning for Classification, Regression, and Generation in Jet Physics
title_fullStr Advanced Machine Learning for Classification, Regression, and Generation in Jet Physics
title_full_unstemmed Advanced Machine Learning for Classification, Regression, and Generation in Jet Physics
title_short Advanced Machine Learning for Classification, Regression, and Generation in Jet Physics
title_sort advanced machine learning for classification, regression, and generation in jet physics
topic EP-IT Data science seminars
url http://cds.cern.ch/record/2292926
work_keys_str_mv AT nachmanben advancedmachinelearningforclassificationregressionandgenerationinjetphysics