Zeroth- and first-order difference discrimination for unsupervised domain adaptation
Abstract Unsupervised domain adaptation transfers empirical knowledge from a label-rich source domain to a fully unlabeled target domain with a different distribution. A core idea of many existing approaches is to reduce the distribution divergence between domains. However, they focused only on part...
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| Principais autores: | , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Springer
2023-12-01
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| Serier: | Complex & Intelligent Systems |
| Fag: | |
| Online adgang: | https://doi.org/10.1007/s40747-023-01283-1 |
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