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Exploring End-to-end Deep Learning Applications for Event Classification at CMS
An essential part of new physics searches at the Large Hadron Collider (LHC) at CERN involves event classification, or distinguishing potential signal events from those coming from background processes. Current machine learning techniques accomplish this using traditional hand-engineered features li...
| Autores principales: | , , , |
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| Lenguaje: | eng |
| Publicado: |
2018
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1051/epjconf/201921406031 http://cds.cern.ch/record/2650365 |