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ORCIDHEPML@NIPS 2014: Montreal, Quebec, Canada
- Workshop on High-energy Physics and Machine Learning, HEPML 2014, held at NIPS 2014, Montreal, Quebec, Canada, December 8-13, 2014. JMLR Workshop and Conference Proceedings 42, JMLR.org 2014
Accepted Papers
- Vladimir V. Gligorov:
Real-time data analysis at the LHC: present and future. 1-18 - Claire Adam-Bourdarios, Glen Cowan, Cécile Germain, Isabelle Guyon, Balázs Kégl, David Rousseau:
The Higgs boson machine learning challenge. 19-55 - Gábor Melis:
Dissecting the Winning Solution of the HiggsML Challenge. 57-67 - Tianqi Chen, Tong He:
Higgs Boson Discovery with Boosted Trees. 69-80 - Peter J. Sadowski, Julian Collado, Daniel Whiteson, Pierre Baldi:
Deep Learning, Dark Knowledge, and Dark Matter. 81-87 - Wojciech Kotlowski:
Consistent optimization of AMS by logistic loss minimization. 99-108 - Roberto Díaz-Morales, Ángel Navia-Vázquez:
Optimization of AMS using Weighted AUC optimized models. 109-127 - Lester W. Mackey, Jordan Bryan, Man Yue Mo:
Weighted Classification Cascades for Optimizing Discovery Significance in the HiggsML Challenge. 129-134
Preface
- Preface. S2014
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