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Improving Unsupervised Domain Adaptation with Mixup Training

Unsupervised domain adaptation studies the problem of utilizing a relevant source domain with abundant labels to build predictive modeling for an unannotated target domain.

Data and Resources

Cite this as

Shen Yan, Huan Song, Nanxiang Li, Lincan Zou, Liu Ren (2024). Dataset: Improving Unsupervised Domain Adaptation with Mixup Training. https://doi.org/10.57702/wnqqwqtk

DOI retrieved: December 16, 2024

Additional Info

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2001.00677
Author Shen Yan
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Huan Song
Nanxiang Li
Lincan Zou
Liu Ren