Fengrui Liu

For Internet-based service companies, anomaly detection on data streams is critical in troubleshooting, seeking to maintain service quality and reliability. Most of known detection methods have an underlying assumption that the data are always continuous. In practical applications, however, we learn that many real-world data are sporadic. It incurs particular challenges for the task of anomaly detection, for which the common preprocessing of downsampling on sporadic data can omit potential anomalies and delay alarms.