Unraveling the ‘anomaly’ in time series anomaly detection: A self-supervised tri-domain solution
The ongoing challenges in time series anomaly detection (TSAD), including the scarcity of anomaly labels and the variability in anomaly lengths and shapes, have led to the need for a more robust and efficient solution. As limited anomaly labels hinder traditional supervised models in anomaly detecti...
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格式: | text |
語言: | English |
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Institutional Knowledge at Singapore Management University
2024
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在線閱讀: | https://ink.library.smu.edu.sg/sis_research/9282 https://ink.library.smu.edu.sg/context/sis_research/article/10282/viewcontent/2311.11235v2.pdf |
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機構: | Singapore Management University |
語言: | English |