Aug 2 – 6, 2021
Europe/Brussels timezone

RanBox: Anomaly Detection in the Copula Space

Aug 5, 2021, 9:00 AM


Parallel contribution H. Statistical Methods for Physics Analysis in the XXI Century Parallels Track H


Tommaso Dorigo (INFN Padova)


The unsupervised search for overdense regions in high-dimensional feature spaces, where locally high population densities may be associated with anomalous contaminations to an otherwise more uniform population, is of relevance to applications ranging from fundamental research to industrial use cases. Motivated by the specific needs of searches for new phenomena in particle collisions, we propose a novel approach that targets signals of interest populating compact regions of the feature space. The method consists in a systematic scan of subspaces of a standardized copula of the feature space, where the minimum p-value of a hypothesis test of local uniformity is sought by gradient descent. We characterize the performance of the proposed algorithm and show its effectiveness in several experimental situations.

Primary author

Tommaso Dorigo (INFN Padova)

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