Classification without labels: learning from mixed samples in high energy physics

Modern machine learning techniques can be used to construct powerful models for difficult collider physics problems. In many applications, however, these models are trained on imperfect simulations due to a lack of truth-level information in the data, which risks the model learning artifacts of the...

Full description

Bibliographic Details
Main Authors: Nachman, Benjamin (Author), Metodiev, Eric Mario (Contributor), Thaler, Jesse (Contributor)
Other Authors: Massachusetts Institute of Technology. Center for Theoretical Physics (Contributor), Massachusetts Institute of Technology. Department of Physics (Contributor)
Format: Article
Language:English
Published: Springer Berlin Heidelberg, 2017-12-08T23:23:08Z.
Subjects:
Online Access:Get fulltext