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JMLR Workshop and Conference Proceedings

Volume 42: NIPS 2014 Workshop on High-energy Physics and Machine Learning

Editors: Glen Cowan, Cécile Germain, Isabelle Guyon, Balázs Kégl, David Rousseau

Contents:

Preface

Preface

The Editors

Accepted Papers

Real-time data analysis at the LHC: present and future

Vladimir Gligorov

The Higgs boson machine learning challenge

Claire Adam-Bourdarios, Glen Cowan, Cécile Germain, Isabelle Guyon, Balàzs Kégl, David Rousseau

Dissecting the Winning Solution of the HiggsML Challenge

Gábor Melis

Higgs Boson Discovery with Boosted Trees

Tianqi Chen, Tong He

Deep Learning, Dark Knowledge, and Dark Matter

Peter Sadowski, Julian Collado, Daniel Whiteson, Pierre Baldi

Consistent optimization of AMS by logistic loss minimization

Wojciech Kotłowski

Optimization of AMS using Weighted AUC optimized models

Roberto Díaz-Morales, Ángel Navia-Vázquez

Weighted Classification Cascades for Optimizing Discovery Significance in the HiggsML Challenge

Lester Mackey, Jordan Bryan, Man Yue Mo