publication . Report . 2018

Deep Representation Learning for Trigger Monitoring

Hussain, Aman;
Open Access
  • Published: 28 Sep 2018
  • Publisher: Zenodo
We propose a novel neural network architecture called Hierarchical Latent Autoencoder to exploit the underlying hierarchical nature of the CMS Trigger System for data quality monitoring. Given the hierarchical cascaded design of the CMS Trigger System, the central idea is to learn the probability distribution of the Level 1 Triggers, modelled as the hidden archetypes, from the observable High Level Triggers. During evaluation, the learned parameters of the latent distribution can be used to generate a reconstruction probability score. We propose to use this probability metric for anomaly detection since a bounded number from zero to one has better interpretabili...
free text keywords: CERN openlab, summer student programme, CERN openlab, summer student programme
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