50 citations · 52 across the 3 of their papers we have counts for
3 papers
Combining inherent knowledge of vision-language models with unsupervised domain adaptation through strong-weak guidance
Thomas Westfechtel, Dexuan Zhang, Tatsuya Harada
Unsupervised domain adaptation (UDA) tries to overcome the tedious work of labeling data by leveraging a labeled source dataset and transferring its knowledge to a similar but diff…
Gradual Source Domain Expansion for Unsupervised Domain Adaptation
Thomas Westfechtel, Hao-Wei Yeh, Dexuan Zhang +1
Unsupervised domain adaptation (UDA) tries to overcome the need for a large labeled dataset by transferring knowledge from a source dataset, with lots of labeled data, to a target…
Adversarial Dropout Regularization
Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada +1
We present a method for transferring neural representations from label-rich source domains to unlabeled target domains. Recent adversarial methods proposed for this task learn to a…