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20192021
most citedSubtype-aware Unsupervised Domain Adaptation for Medical Diagnosis

8 citations · 18 across the 6 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.CV2021

Recursively Conditional Gaussian for Ordinal Unsupervised Domain Adaptation

Xiaofeng Liu, Site Li, Yubin Ge +3

The unsupervised domain adaptation (UDA) has been widely adopted to alleviate the data scalability issue, while the existing works usually focus on classifying independently discre…

cs.LG20211 cited

Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference

Xiaofeng Liu, Bo Hu, Linghao Jin +6

In this work, we propose a domain generalization (DG) approach to learn on several labeled source domains and transfer knowledge to a target domain that is inaccessible in training…

cs.CV20218 cited

Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis

Xiaofeng Liu, Xiongchang Liu, Bo Hu +7

Recent advances in unsupervised domain adaptation (UDA) show that transferable prototypical learning presents a powerful means for class conditional alignment, which encourages the…

cs.CV20212 cited

Identity-aware Facial Expression Recognition in Compressed Video

Xiaofeng Liu, Linghao Jin, Xu Han +3

This paper targets to explore the inter-subject variations eliminated facial expression representation in the compressed video domain. Most of the previous methods process the RGB…

cs.CV20213 cited

Energy-constrained Self-training for Unsupervised Domain Adaptation

Xiaofeng Liu, Bo Hu, Xiongchang Liu +3

Unsupervised domain adaptation (UDA) aims to transfer the knowledge on a labeled source domain distribution to perform well on an unlabeled target domain. Recently, the deep self-t…