Unsupervised domain adaptation through transferring both the source-knowledge and target-relatedness simultaneously
Unsupervised domain adaptation (UDA) is an emerging research topic in the field of machine learning and pattern recognition, which aims to help the learning of unlabeled target domain by transferring knowledge from the source domain. To perform UDA, a variety of methods have been proposed, most of w...
Main Authors: | Qing Tian, Yanan Zhu, Yao Cheng, Chuang Ma, Meng Cao |
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Format: | Article |
Language: | English |
Published: |
AIMS Press
2023-01-01
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Series: | Electronic Research Archive |
Subjects: | |
Online Access: | https://www.aimspress.com/article/doi/10.3934/era.2023060?viewType=HTML |
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