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Volume 42: NIPS 2014 Workshop on High-energy Physics and Machine Learning, 13 December 2014, Montreal, Canada
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Editors: Glen Cowan, Cécile Germain, Isabelle Guyon, Balázs Kégl, David Rousseau
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Preface
Accepted Papers
Real-time data analysis at the LHC: present and future
Vladimir Gligorov;
PMLR 42:1-18
[abs][Download PDF]
The Higgs boson machine learning challenge
Claire Adam-Bourdarios, Glen Cowan, Cécile Germain, Isabelle Guyon, Balàzs Kégl, David Rousseau;
PMLR 42:19-55
[abs][Download PDF]
Dissecting the Winning Solution of the HiggsML Challenge
Gábor Melis;
PMLR 42:57-67
[abs][Download PDF]
Higgs Boson Discovery with Boosted Trees
Tianqi Chen, Tong He;
PMLR 42:69-80
[abs][Download PDF]
Deep Learning, Dark Knowledge, and Dark Matter
Peter Sadowski, Julian Collado, Daniel Whiteson, Pierre Baldi;
PMLR 42:81-87
[abs][Download PDF]
Consistent optimization of AMS by logistic loss minimization
Wojciech Kotłowski;
PMLR 42:99-108
[abs][Download PDF]
Optimization of AMS using Weighted AUC optimized models
Roberto Díaz-Morales, Ángel Navia-Vázquez;
PMLR 42:109-127
[abs][Download PDF]
Weighted Classification Cascades for Optimizing Discovery Significance in the HiggsML
Challenge
Lester Mackey, Jordan Bryan, Man Yue Mo;
PMLR 42:129-134
[abs][Download PDF]