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Volume 321 - Sixth Annual Conference on Large Hadron Collider Physics (LHCP2018) - Posters
Machine learning techniques for heavy flavour identification
B. Chazin Quero* on behalf of the CMS collaboration
*corresponding author
Full text: pdf
Pre-published on: 2018 October 01
Published on:
Abstract
Reliable and performant heavy flavour identification is of prime importance for the physics
program of the CMS experiment. During the last years the CMS collaboration has dedicated a
considerable effort to improve and expand its capabilities in this sector by applying several
machine learning techniques well established in industry, but still experimental in HEP. The
poster will focus on a selection of these techniques and describe the implementation details as
well as the resulting gains.
Open Access
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