Orateur
Louis Moureaux
(Universität Hamburg)
Description
Despite strong motivation from theory and an intensive search
programme, no particle beyond the standard model has been
discovered at the LHC. Since model specific searches cannot
test every possible signal model, a broader approach capable
of testing many hypotheses at once is needed. Anomaly
detection refers to the set of machine-learning methods
specifically designed for this purpose.
Starting from anomaly detection approaches used in industry
and the classical bump hunt, we will show how to construct
anomaly detection methods and review the first round of
experimental results.