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Bayesian Optimization for machine learning algorithms in the context of Higgs searches at the CMS experiment
Machine Learning algorithms, such as Boosted Decisions Trees and Deep Neural Network, are widely used in High-Energy-Physics. The aim of this study is to apply Bayesian Optimization to tune the hyperparameters used in a machine learning algorithm. This algorithm performs an energy regression process...
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| Lenguaje: | eng |
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2019
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| Acceso en línea: | http://cds.cern.ch/record/2702355 |