Sequential Anomaly Detection in the Presence of Noise and Limited Feedback
Sequential Anomaly Detection in the Presence of Noise and Limited Feedback
This paper describes a methodology for detecting anomalies from sequentially observed and potentially noisy data. The proposed approach consists of two main elements: (1) {\em filtering}, or assigning a belief or likelihood to each successive measurement based upon our ability to predict it from previous noisy observations, and (2) {\em …