Speaker
David Walter
(CERN)
Description
In this talk we will discuss previous measurements using binned maximum likelihood unfolding focusing on analyses with large numbers of bins and nuisance parameters. We will outline the technical implementation and highlight the challenges and limitations. Furthermore, we showcase the newly-developed approach of "linearized binned likelihood unfolding",
a modified formalism that has a better scaling and allows to perform unfolding on even larger numbers of bins and nuisance parameters.
Author
David Walter
(CERN)
Co-authors
Josh Bendavid
(Massachusetts Inst. of Technology (US))
Matteo Defranchis
(CERN)
