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.

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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

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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