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