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ML Techniques for heavy flavour identification in CMS
<!--HTML-->Jet flavour identification is a fundamental component for the physics program of the LHC-based experiments. The presence of multiple flavours to be identified leads to a multiclass classification problem. Moreover, the classification of boosted jets has acquired an increasing import...
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Lenguaje: | eng |
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2019
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2672563 |
Sumario: | <!--HTML-->Jet flavour identification is a fundamental component for the physics program of the LHC-based experiments. The presence of multiple flavours to be identified leads to a multiclass classification problem. Moreover, the classification of boosted jets has acquired an increasing importance in the physics program of CMS. In this presentation we will present the performance on both simulated and real data of our latest resolved and boosted heavy flavour taggers as well as the future prospects for the evolution of these techniques and the technical strategies adopted to deploy them in the harsh computing environment of a large-scale HEP computing software stack. |
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