Low-Rank Optimal Transport for Robust Domain Adaptation

doi:10.1109/JAS.2024.124344

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	Low-Rank Optimal Transport for Robust Domain Adaptation
	Bingrong Xu; Jianhua Yin; Cheng Lian; Yixin Su; Zhigang Zeng
发表期刊	IEEE/CAA Journal of Automatica Sinica
ISSN	2329-9266
	2024
卷号	11 期号:7 页码:1667-1680
摘要	When encountering the distribution shift between the source (training) and target (test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot of success both in theory and practice under the assumption that all the examples in the source domain are well-labeled and of high quality. However, the methods consistently lose robustness in noisy settings where data from the source domain have corrupted labels or features which is common in reality. Therefore, robust domain adaptation has been introduced to deal with such problems. In this paper, we attempt to solve two interrelated problems with robust domain adaptation: distribution shift across domains and sample noises of the source domain. To disentangle these challenges, an optimal transport approach with low-rank constraints is applied to guide the domain adaptation model training process to avoid noisy information influence. For the domain shift problem, the optimal transport mechanism can learn the joint data representations between the source and target domains using a measurement of discrepancy and preserve the discriminative information. The rank constraint on the transport matrix can help recover the corrupted subspace structures and eliminate the noise to some extent when dealing with corrupted source data. The solution to this relaxed and regularized optimal transport framework is a convex optimization problem that can be solved using the Augmented Lagrange Multiplier method, whose convergence can be mathematically proved. The effectiveness of the proposed method is evaluated through extensive experiments on both synthetic and real-world datasets.
关键词	Domain adaptation low-rank constraint noise corruption optimal transport
DOI	10.1109/JAS.2024.124344
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/57310
专题	学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Bingrong Xu,Jianhua Yin,Cheng Lian,et al. Low-Rank Optimal Transport for Robust Domain Adaptation[J]. IEEE/CAA Journal of Automatica Sinica,2024,11(7):1667-1680.
APA	Bingrong Xu,Jianhua Yin,Cheng Lian,Yixin Su,&Zhigang Zeng.(2024).Low-Rank Optimal Transport for Robust Domain Adaptation.IEEE/CAA Journal of Automatica Sinica,11(7),1667-1680.
MLA	Bingrong Xu,et al."Low-Rank Optimal Transport for Robust Domain Adaptation".IEEE/CAA Journal of Automatica Sinica 11.7(2024):1667-1680.

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