Machine Learning for Jet Physics

Modern jet machine-learning classification in real time (20'+5')

15 Nov 2018, 17:05

25m

One West (WH1W) (Fermilab)

Experimental/Practical aspects of learning with jets (Chairs: Ben Hooberman and Daniel Elvira)

Speaker

Konstantin Gizdov (The University of Edinburgh (GB))

Description

We demonstrate the ability to create drone from a wide range of classifiers, with a particular emphasis on the application to modern jet classification. Machine learning is increasingly dominating the preferred tool for the classification of jets. However, as experiment data rates increase by orders of magnitude, such technologies become expensive in terms of time and performance. In light of this, we present a method and toolkit for creating a drone classifier from any machine learning classifier, preserving the accuracy, precision, and specificity, but greatly improving on algorithm execution performance.