Toward Automated Anomaly Identification in Large-Scale Systems

When a system fails to function properly, health-related data are collected for troubleshooting. However, it is challenging to effectively identify anomalies from the voluminous amount of noisy, high-dimensional data. The traditional manual approach is time-consuming, error-prone, and even worse, no...

Ausführliche Beschreibung