The Higgs Machine Learning Challenge

The Higgs Machine Learning Challenge was an open data analysis competition that took place between May and September 2014. Samples of simulated data from the ATLAS Experiment at the LHC corresponding to signal events with Higgs bosons decaying to τ+τ- together with background events were made availa...

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Bibliographic Details
Published in:Journal of physics. Conference series 2015-12, Vol.664 (7), p.72015
Main Authors: Adam-Bourdarios, C, Cowan, G, Germain-Renaud, C, Guyon, I, Kégl, B, Rousseau, D
Format: Article
Language:English
Subjects:
Bosons
Data analysis
Higgs bosons
Large Hadron Collider
Machine learning
Physics
Signal processing
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Summary:The Higgs Machine Learning Challenge was an open data analysis competition that took place between May and September 2014. Samples of simulated data from the ATLAS Experiment at the LHC corresponding to signal events with Higgs bosons decaying to τ+τ- together with background events were made available to the public through the website of the data science organization Kaggle (kaggle.com). Participants attempted to identify the search region in a space of 30 kinematic variables that would maximize the expected discovery significance of the signal process. One of the primary goals of the Challenge was to promote communication of new ideas between the Machine Learning (ML) and HEP communities. In this regard it was a resounding success, with almost 2,000 participants from HEP, ML and other areas. The process of understanding and integrating the new ideas, particularly from ML into HEP, is currently underway.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/664/7/072015