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Talk1 h 7 min

II - Multivariate Classification and Machine Learning in HEP

Thomas KECK · CERN

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About

A summary of the history of deep-learning is given and the difference to traditional artificial neural networks is discussed. Advanced methods like convoluted neural networks, recurrent neural networks and unsupervised training are introduced. Interesting examples from this emerging field outside HEP are presented. Possible applications in HEP are discussed..

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The talk

  1. II - Multivariate Classification and Machine Learning in HEP 2016-03-01 · 1 h 7 min · CERN's player

Credits and licence

Institution
CERN
Department
inverted CSC
Speaker
Thomas KECK
Year
2016
Language
English
Subjects
Computer science
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
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