The Higgs boson machine learning challenge

Claire Adam-Bourdarios, Glen Cowan, Cécile Germain, Isabelle Guyon, Balàzs Kégl, David Rousseau
Proceedings of the NIPS 2014 Workshop on High-energy Physics and Machine Learning, PMLR 42:19-55, 2015.

Abstract

The Higgs Boson Machine Learning Challenge (HiggsML or the Challenge for short) was organized to promote collaboration between high energy physicists and data scientists. The ATLAS experiment at CERN provided simulated data that has been used by physicists in a search for the Higgs boson. The Challenge was organized by a small group of ATLAS physicists and data scientists. It was hosted by Kaggle at \urlhttps://www.kaggle.com/c/higgs-boson; the challenge data is now available on \url\opendataLink. This paper provides the physics background and explains the challenge setting, the challenge design, and analyzes its results.

Cite this Paper

BibTeX
@InProceedings{pmlr-v42-cowa14, title = {The {H}iggs boson machine learning challenge}, author = {Adam-Bourdarios, Claire and Cowan, Glen and Germain, Cécile and Guyon, Isabelle and Kégl, Balàzs and Rousseau, David}, booktitle = {Proceedings of the NIPS 2014 Workshop on High-energy Physics and Machine Learning}, pages = {19--55}, year = {2015}, editor = {Cowan, Glen and Germain, Cécile and Guyon, Isabelle and Kégl, Balázs and Rousseau, David}, volume = {42}, series = {Proceedings of Machine Learning Research}, address = {Montreal, Canada}, month = {13 Dec}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v42/cowa14.pdf}, url = {https://proceedings.mlr.press/v42/cowa14.html}, abstract = {The Higgs Boson Machine Learning Challenge (HiggsML or the Challenge for short) was organized to promote collaboration between high energy physicists and data scientists. The ATLAS experiment at CERN provided simulated data that has been used by physicists in a search for the Higgs boson. The Challenge was organized by a small group of ATLAS physicists and data scientists. It was hosted by Kaggle at \urlhttps://www.kaggle.com/c/higgs-boson; the challenge data is now available on \url\opendataLink. This paper provides the physics background and explains the challenge setting, the challenge design, and analyzes its results.} }
Endnote
%0 Conference Paper %T The Higgs boson machine learning challenge %A Claire Adam-Bourdarios %A Glen Cowan %A Cécile Germain %A Isabelle Guyon %A Balàzs Kégl %A David Rousseau %B Proceedings of the NIPS 2014 Workshop on High-energy Physics and Machine Learning %C Proceedings of Machine Learning Research %D 2015 %E Glen Cowan %E Cécile Germain %E Isabelle Guyon %E Balázs Kégl %E David Rousseau %F pmlr-v42-cowa14 %I PMLR %P 19--55 %U https://proceedings.mlr.press/v42/cowa14.html %V 42 %X The Higgs Boson Machine Learning Challenge (HiggsML or the Challenge for short) was organized to promote collaboration between high energy physicists and data scientists. The ATLAS experiment at CERN provided simulated data that has been used by physicists in a search for the Higgs boson. The Challenge was organized by a small group of ATLAS physicists and data scientists. It was hosted by Kaggle at \urlhttps://www.kaggle.com/c/higgs-boson; the challenge data is now available on \url\opendataLink. This paper provides the physics background and explains the challenge setting, the challenge design, and analyzes its results.
RIS
TY - CPAPER TI - The Higgs boson machine learning challenge AU - Claire Adam-Bourdarios AU - Glen Cowan AU - Cécile Germain AU - Isabelle Guyon AU - Balàzs Kégl AU - David Rousseau BT - Proceedings of the NIPS 2014 Workshop on High-energy Physics and Machine Learning DA - 2015/08/27 ED - Glen Cowan ED - Cécile Germain ED - Isabelle Guyon ED - Balázs Kégl ED - David Rousseau ID - pmlr-v42-cowa14 PB - PMLR DP - Proceedings of Machine Learning Research VL - 42 SP - 19 EP - 55 L1 - http://proceedings.mlr.press/v42/cowa14.pdf UR - https://proceedings.mlr.press/v42/cowa14.html AB - The Higgs Boson Machine Learning Challenge (HiggsML or the Challenge for short) was organized to promote collaboration between high energy physicists and data scientists. The ATLAS experiment at CERN provided simulated data that has been used by physicists in a search for the Higgs boson. The Challenge was organized by a small group of ATLAS physicists and data scientists. It was hosted by Kaggle at \urlhttps://www.kaggle.com/c/higgs-boson; the challenge data is now available on \url\opendataLink. This paper provides the physics background and explains the challenge setting, the challenge design, and analyzes its results. ER -
APA
Adam-Bourdarios, C., Cowan, G., Germain, C., Guyon, I., Kégl, B. & Rousseau, D.. (2015). The Higgs boson machine learning challenge. Proceedings of the NIPS 2014 Workshop on High-energy Physics and Machine Learning, in Proceedings of Machine Learning Research 42:19-55 Available from https://proceedings.mlr.press/v42/cowa14.html.

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