Efficient Multivariate Time Series Anomaly Detection Through Transfer Learning for Large-Scale Software Systems

Timely anomaly detection of multivariate time series (MTS) is of vital importance for managing large-scale software systems. However, many deep learning-based MTS anomaly detection models require long-term MTS training data to achieve optimal performance, which often conflicts with the frequent patt...

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Veröffentlicht in:	ACM transactions on software engineering and methodology 2024-11
Hauptverfasser:	Sun, Yongqian, Liang, Minghan, Zhang, Shenglin, Che, Zeyu, Luo, Zhiyao, Li, Dongwen, Zhang, Yuzhi, Pei, Dan, Pan, Lemeng, Hou, Liping
Format:	Artikel
Sprache:	eng
Schlagworte:	Computing methodologies Computing methodologies / Machine learning Computing methodologies / Machine learning / Learning paradigms Computing methodologies / Machine learning / Learning paradigms / Unsupervised learning Computing methodologies / Machine learning / Learning paradigms / Unsupervised learning / Anomaly detection Computing methodologies / Machine learning / Machine learning approaches Computing methodologies / Machine learning / Machine learning approaches / Kernel methods Computing methodologies / Machine learning / Machine learning approaches / Learning in probabilistic graphical models Hardware Hardware / Power and energy Information systems Information systems / Information systems applications Information systems / Information systems applications / Data mining Software and its engineering Software and its engineering / Software notations and tools Software and its engineering / Software notations and tools / Software libraries and repositories
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