Chaoliang Zhong — accepted AI-conference papers

2022

Learning Unforgotten Domain-Invariant Representations for Online Unsupervised Domain Adaptation

Cheng Feng, Chaoliang Zhong, Jie Wang, Ying Zhang, Jun Sun, Yasuto Yokota

IJCAI 2022poster

Existing unsupervised domain adaptation (UDA) studies focus on transferring knowledge in an offline manner. However, many tasks involve online requirements, especially in real-time systems. In this paper, we discuss Online UDA (OUDA) which assumes that the target samples are arriving sequentially as…

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2021

Gradient Distribution Alignment Certificates Better Adversarial Domain Adaptation

Zhiqiang Gao, Shufei Zhang, Kaizhu Huang, Qiufeng Wang, Chaoliang Zhong

ICCV 2021poster

The latest heuristic for handling the domain shift in unsupervised domain adaptation tasks is to reduce the data distribution discrepancy using adversarial learning. Recent studies improve the conventional adversarial domain adaptation methods with discriminative information by integrating the class…

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