Semi-Supervised Domain Adaptation with Source Label Adaptation

Author:

Yu Yu-Chu1,Lin Hsuan-Tien1

Affiliation:

1. National Taiwan University

Publisher

IEEE

Reference38 articles.

1. Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation;liang;International Conference on Machine Learning,0

2. Semi-supervised models are strong unsupervised domain adaptation learners;zhang;ArXiv Preprint,2021

3. Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation

4. Understanding deep learning (still) requires rethinking generalization

5. Unsupervised domain adaptation with residual transfer networks;long;Advances in neural information processing systems,2016

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