RGLD: Randomized Global-Local Density Estimation for Tabular Anomaly Detection

Quanling Zhao, Jiaying Yang, Ye Tian +5

Unsupervised tabular anomaly detection requires methods that are accurate, robust across heterogeneous datasets, and computationally efficient. Classical statistical detectors are…