no code implementations • 31 Jul 2022 • Debanjan Datta, Sathappan Muthiah, John Simeone, Amelia Meadows, Naren Ramakrishnan
The task of finding such fraudulent activities using trade data, in the absence of ground truth, can be modelled as an unsupervised anomaly detection problem.
no code implementations • 29 Jun 2022 • Debanjan Datta, Feng Chen, Naren Ramakrishnan
We present an approach -- Context preserving Algorithmic Recourse for Anomalies in Tabular data (CARAT), that is effective, scalable, and agnostic to the underlying anomaly detection model.
no code implementations • 2 Apr 2021 • Debanjan Datta, Sathappan Muthiah, Naren Ramakrishnan
Among other challenges annotations are unavailable for our large-scale trade data with heterogeneous features (categorical and continuous), that can assist in building automated systems to detect fraudulent transactions.
no code implementations • 9 Nov 2020 • Debanjan Datta
A small survey on event detection using Twitter.