Virtual Mixup Training for Unsupervised Domain Adaptation

10 May 2019Xudong MaoYun MaZhenguo YangYangbin ChenQing Li

We study the problem of unsupervised domain adaptation which aims to adapt models trained on a labeled source domain to a completely unlabeled target domain. Recently, the cluster assumption has been applied to unsupervised domain adaptation and achieved strong performance... (read more)

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