Adversarial domain adaptation to reduce sample bias of a high energy physics classifier

no code implementations • 1 May 2020 • Jose M. Clavijo, Paul Glaysher, Judith M. Katzy, Jenia Jitsev

We apply adversarial domain adaptation in unsupervised setting to reduce sample bias in a supervised high energy physics events classifier training.

BIG-bench Machine Learning Classification +3

Iterative subtraction method for Feature Ranking

no code implementations • 13 Jun 2019 • Paul Glaysher, Judith M. Katzy, Sitong An

Ranking methods, such as the BDT Selection Frequency commonly used in High Energy Physics and the Permutational Performance, are compared with the computationally expense Iterative Addition and Iterative Removal procedures, while the latter was found to be the most performant.

Classification General Classification