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20202022
most citedUnsupervised Domain Adaptation via Discriminative Manifold Propagation

100 citations · 118 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2022

Maximizing Conditional Independence for Unsupervised Domain Adaptation

Yi-Ming Zhai, You-Wei Luo

Unsupervised domain adaptation studies how to transfer a learner from a labeled source domain to an unlabeled target domain with different distributions. Existing methods mainly fo…

cs.LG2022

Generalized Label Shift Correction via Minimum Uncertainty Principle: Theory and Algorithm

You-Wei Luo, Chuan-Xian Ren

As a fundamental problem in machine learning, dataset shift induces a paradigm to learn and transfer knowledge under changing environment. Previous methods assume the changes are i…

cs.LG20211 cited

Conditional Bures Metric for Domain Adaptation

You-Wei Luo, Chuan-Xian Ren

As a vital problem in classification-oriented transfer, unsupervised domain adaptation (UDA) has attracted widespread attention in recent years. Previous UDA methods assume the mar…

cs.LG2020100 cited

Unsupervised Domain Adaptation via Discriminative Manifold Propagation

You-Wei Luo, Chuan-Xian Ren, Dao-Qing Dai +1

Unsupervised domain adaptation is effective in leveraging rich information from a labeled source domain to an unlabeled target domain. Though deep learning and adversarial strategy…

cs.CV202017 cited

Discriminative Residual Analysis for Image Set Classification with Posture and Age Variations

Chuan-Xian Ren, You-Wei Luo, Xiao-Lin Xu +2

Image set recognition has been widely applied in many practical problems like real-time video retrieval and image caption tasks. Due to its superior performance, it has grown into…

cs.LG2020

Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment

You-Wei Luo, Chuan-Xian Ren, Pengfei Ge +2

Unsupervised domain adaptation is effective in leveraging the rich information from the source domain to the unsupervised target domain. Though deep learning and adversarial strate…