3 citations · 3 across the 2 of their papers we have counts for
6 papers
MLaaS4HEP: Machine Learning as a Service for HEP
Valentin Kuznetsov, Luca Giommi, Daniele Bonacorsi
Machine Learning (ML) will play a significant role in the success of the upcoming High-Luminosity LHC (HL-LHC) program at CERN. An unprecedented amount of data at the exascale will…
Extension of the INFN Tier-1 on a HPC system
Tommaso Boccali, Stefano Dal Pra, Daniele Spiga +10
The INFN Tier-1 located at CNAF in Bologna (Italy) is a center of the WLCG e-Infrastructure, supporting the 4 major LHC collaborations and more than 30 other INFN-related experimen…
Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach
Leticia Decker, Daniel Leite, Luca Giommi +1
Detection of anomalous behaviors in data centers is crucial to predictive maintenance and data safety. With data centers, we mean any computer network that allows users to transmit…
Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers
Leticia Decker, Daniel Leite, Fabio Viola +1
Log-based predictive maintenance of computing centers is a main concern regarding the worldwide computing grid that supports the CERN (European Organization for Nuclear Research) p…
Machine Learning in High Energy Physics Community White Paper
Kim Albertsson, Piero Altoe, Dustin Anderson +125
Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by a…
Exploiting Apache Spark platform for CMS computing analytics
Marco Meoni, Valentin Kuznetsov, Luca Menichetti +3
The CERN IT provides a set of Hadoop clusters featuring more than 5 PBytes of raw storage with different open-source, user-level tools available for analytical purposes. The CMS ex…