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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.

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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

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Additional Info

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