Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data

no code implementations • 23 Apr 2024 • Dayananda Herurkar, Sebastian Palacio, Ahmed Anwar, Joern Hees, Andreas Dengel

Anomaly detection in real-world scenarios poses challenges due to dynamic and often unknown anomaly distributions, requiring robust methods that operate under an open-world assumption.

Anomaly Detection Federated Learning +2

Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data

no code implementations • 21 Sep 2022 • Timur Sattarov, Dayananda Herurkar, Jörn Hees

We find that denoising autoencoders applied to this task already outperform other approaches in the cell error detection rates as well as in the expected value rates.

Decision Making Denoising +2

RECol: Reconstruction Error Columns for Outlier Detection

no code implementations • 4 Feb 2021 • Jörn Hees, Dayananda Herurkar, Mario Meier

Detecting outliers or anomalies is a common data analysis task.

Outlier Detection