Semi-supervised anomaly detection with contamination-resilience and incremental training
Anomaly detection plays a vital role in various realistic applications, including fraud
detection, network traffic analysis, medical diagnosis, and so on. Semi-supervised anomaly …
detection, network traffic analysis, medical diagnosis, and so on. Semi-supervised anomaly …
A comprehensive analysis of concept drift locality in data streams
Adapting to drifting data streams is a significant challenge in online learning. Concept drift
must be detected for effective model adaptation to evolving data properties. Concept drift …
must be detected for effective model adaptation to evolving data properties. Concept drift …
Network security AIOps for online stream data monitoring
In cybersecurity, live production data for predictive analysis pose a significant challenge due
to the inherently secure nature of the domain. Although there are publicly available …
to the inherently secure nature of the domain. Although there are publicly available …