A survey on explainable anomaly detection
In the past two decades, most research on anomaly detection has focused on improving the
accuracy of the detection, while largely ignoring the explainability of the corresponding …
accuracy of the detection, while largely ignoring the explainability of the corresponding …
{Jump-Starting} multivariate time series anomaly detection for online service systems
With the booming of online service systems, anomaly detection on multivariate time series,
such as a combination of CPU utilization, average response time, and requests per second …
such as a combination of CPU utilization, average response time, and requests per second …
Efficient kpi anomaly detection through transfer learning for large-scale web services
Timely anomaly detection of key performance indicators (KPIs), eg, service response time,
error rate, is of utmost importance to Web services. Over the years, many unsupervised deep …
error rate, is of utmost importance to Web services. Over the years, many unsupervised deep …
Consistent anomaly detection and localization of multivariate time series via cross-correlation graph-based encoder–decoder GAN
H Liang, L Song, J Du, X Li… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Multivariate time series is widely derived from industrial facilities, such as power plants,
manufacturing machines, spacecraft, digital devices, and so on, and anomaly detection and …
manufacturing machines, spacecraft, digital devices, and so on, and anomaly detection and …
Unsupervised online anomaly detection with parameter adaptation for KPI abrupt changes
IT companies need to monitor various Key Performance Indicators (KPIs) and detect
anomalies in real time to ensure the quality and reliability of Internet-based services …
anomalies in real time to ensure the quality and reliability of Internet-based services …
Identification of urban functional regions in chengdu based on taxi trajectory time series data
X Liu, Y Tian, X Zhang, Z Wan - ISPRS International Journal of Geo …, 2020 - mdpi.com
Overall scientific planning of urbanization layout is an important component of the new
period of land spatial planning policies. Defining the main functions of different spaces and …
period of land spatial planning policies. Defining the main functions of different spaces and …
Identifying erroneous software changes through self-supervised contrastive learning on time series data
Software changes are frequent and inevitable. How-ever, erroneous software changes may
cause failures and incidents, degrading user experience and system stability. Thus, it is …
cause failures and incidents, degrading user experience and system stability. Thus, it is …
Label-free multivariate time series anomaly detection
Anomaly detection in multivariate time series has been widely studied in one-class
classification (OCC) setting. The training samples in this setting are assumed to be normal …
classification (OCC) setting. The training samples in this setting are assumed to be normal …
Graph embedding-based Anomaly localization for HVAC system
As a major energy consumption system in buildings, anomaly detection on multivariate time
series monitored by sensors in HVAC systems has been a significant challenge. However …
series monitored by sensors in HVAC systems has been a significant challenge. However …
A Review of Approaches for Rapid Data Clustering: Challenges, Opportunities and Future Directions
For organizing and analyzing massive amounts of data and revealing hidden patterns and
structures, clustering is a crucial approach. This paper examines unique strategies for rapid …
structures, clustering is a crucial approach. This paper examines unique strategies for rapid …