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Unsupervised Multi-Task Domain Adaptation
2020 25th International Conference on Pattern Recognition (ICPR), 2021With abundant labeled data, deep convolutional neural networks have shown great success in various image recognition tasks. However, these models are often less powerful when applied to novel datasets due to a phenomenon known as domain shift. Unsupervised domain adaptation methods aim to address this problem, allowing deep models trained on the ...
Shih-Min Yang, Mei-Chen Yeh
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Unsupervised double weighted domain adaptation
Neural Computing and Applications, 2020Domain adaptation can effectively transfer knowledge between domains with different distributions. Most existing methods use distribution alignment to mitigate the domain shift. But they typically align the marginal and conditional distributions with equal weights. This neglects the relative importance of different distribution alignments.
Jingyao Li, Zhanshan Li, Shuai Lü
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On Online Unsupervised Domain Adaptation
2023Recent advances in Artificial Intelligence (AI) have been markedly accelerated by the convergence of advances in Machine Learning (ML) and the exponential growth in computational power. Within this dynamic landscape, the concept of Domain Adaptation (DA) is dedicated to the seamless transference of knowledge across domains characterized by disparate ...
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Structure-Preserved Unsupervised Domain Adaptation
IEEE Transactions on Knowledge and Data Engineering, 2019Domain adaptation has been a primal approach to addressing the issues by lack of labels in many data mining tasks. Although considerable efforts have been devoted to domain adaptation with promising results, most existing work learns a classifier on a source domain and then predicts the labels for target data, where only the instances near the boundary
Hongfu Liu +3 more
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Adversarially robust unsupervised domain adaptation
Artificial IntelligencezbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lianghe Shi, Weiwei Liu
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Deep Unsupervised Convolutional Domain Adaptation
Proceedings of the 25th ACM international conference on Multimedia, 2017In multimedia analysis, the task of domain adaptation is to adapt the feature representation learned in the source domain with rich label information to the target domain with less or even no label information. Significant research endeavors have been devoted to aligning the feature distributions between the source and the target domains in the top ...
Junbao Zhuo +3 more
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Assisted Unsupervised Domain Adaptation
2023 IEEE International Symposium on Information Theory (ISIT), 2023Cheng Chen +3 more
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Distributionally robust unsupervised domain adaptation
Journal of Computational and Applied MathematicszbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yibin Wang, Haifeng Wang
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Smooth unsupervised domain adaptation considering uncertainties
Information Sciences, 2023Mona Moradi +3 more
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Unsupervised Learning Methods for Molecular Simulation Data
Chemical Reviews, 2021Aldo Glielmo +2 more
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