Time series domain adaptation via contrastive adversarial domain disentangled network
Unsupervised domain adaptation is a machine learning framework to transform information learned from one or several source domains with many annotated samples to unlabeled target domains. A typical unsupervised domain adaptation method is typically designed base on visual data. Solutions on time se...
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| 格式: | Thesis-Master by Research |
| 語言: | English |
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Nanyang Technological University
2023
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/168752 |
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