December 13, 2014
Palais des Congrès de Montréal
Europe/Paris timezone

Session

Session 2

Dec 13, 2014, 10:30 AM
Level 5, room 511 c (Palais des Congrès de Montréal)

Level 5, room 511 c

Palais des Congrès de Montréal

Presentation materials

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  1. Gábor Melis
    12/13/14, 10:30 AM
    We describe the winning solution of the HiggsML challenge, the issues related to the evaluation metric and reliable assessment of model performance. Finally, we take a stab at predicting how to achieve larger improvements.
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  2. Tim Salimans
    12/13/14, 10:50 AM
    High Energy Physics provides a challenging data domain with data that is highly structured, but also very noisy. I will present what I have learned analyzing this data for the HiggsML challenge, focusing on methods that are able to effectively search through a high dimensional model space while also achieving good statistical efficiency. In addition, I will discuss the role of the physicist in...
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  3. Tianqi Chen
    12/13/14, 11:10 AM
    In this talk, I will describe how we use principle of gradient boosting method to construct simple and effective regression trees functions for Higgs Boson detection. We take a functional space optimization framework that jointly optimize the training objective and simplicity of functions learnt. I talk about how the objective could be clearly related to the tree searching, pruning and leave...
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  4. Vava Gligorov
    12/13/14, 11:30 AM
    The large hadron collider (LHC), which collides protons at an energy of 14 TeV (for non-physicists, each beam of protons carries roughly the energy of a TGV train going at full speed), produces hundreds of exabytes of data per year, making it one of the largest sources of data in the world today. At present it is not possible to even transfer most of this data from the four main particle...
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