PACWrap: Semi-Supervised PAC Anomaly Detector

Faculty: Insup Lee, Edgar Dobriban, and Oleg Sokolsky

Opportunity: Design a framework that bounds the error rates in anomaly detection. 


Challenge:  How to ensure Probably Approximately Correct  (PAC) guarantee on both the false-negative (FNR) and false-positive (FPR) detection rates for any anomaly detector.


  • Without the need for labeled anomaly data during training