Universal representation learning for multivariate time series using the instance-level and cluster-level supervised contrastive learning
The multivariate time series classification (MTSC) task aims to predict a class label for a given time series. Recently, modern deep learning-based approaches have achieved promising performance over traditional methods for MTSC tasks. The success of these approaches relies on access to the massive...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | Data mining and knowledge discovery. - 2003. - 38(2024), 3 vom: 23. Mai, Seite 1493-1519
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| 1. Verfasser: |
Moradinasab, Nazanin
(VerfasserIn) |
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| Weitere Verfasser: |
Sharma, Suchetha,
Bar-Yoseph, Ronen,
Radom-Aizik, Shlomit,
Bilchick, Kenneth C,
Cooper, Dan M,
Weltman, Arthur,
Brown, Donald E |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | Data mining and knowledge discovery
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| Schlagworte: | Journal Article
Classification
Contrastive learning
Interpretability
Multivariate time series data |
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