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Ruizhi Pu
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When source-free domain adaptation meets learning with noisy labels
L Yi, G Xu, P Xu, J Li, R Pu, C Ling, AI McLeod, B Wang
arXiv preprint arXiv:2301.13381, 2023
512023
Towards more general loss and setting in unsupervised domain adaptation
C Shui, R Pu, G Xu, J Wen, F Zhou, C Gagné, CX Ling, B Wang
IEEE Transactions on Knowledge and Data Engineering 35 (10), 10140-10150, 2023
62023
Generalizing across temporal domains with koopman operators
Q Zeng, W Wang, F Zhou, G Xu, R Pu, C Shui, C Gagné, S Yang, CX Ling, ...
Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 16651 …, 2024
52024
Evolving domain generalization
WW Wang, G Xu, R Pu, J Li, F Zhou, C Shui, C Ling, C Gagné, B Wang
arXiv preprint arXiv:2206.00047, 2022
52022
Label shift conditioned hybrid querying for deep active learning
J Li, H Kong, G Xu, C Shui, R Pu, Z Kang, CX Ling, B Wang
Knowledge-Based Systems 274, 110616, 2023
22023
Yes sir! optimizing semantic space of negatives with self-involvement ranker
R Pu, X Zhang, R Lai, Z Guo, Y Zhang, H Jiang, Y Wu, Y Jia, Z Dou, Z Cao
arXiv preprint arXiv:2109.06436, 2021
22021
Unraveling the Mysteries of Label Noise in Source-Free Domain Adaptation: Theory and Practice
G Xu, L Yi, P Xu, J Li, R Pu, C Shui, C Ling, AI McLeod, B Wang
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025
12025
Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced Regression
R Pu, G Xu, R Fang, B Bao, CX Ling, B Wang
arXiv preprint arXiv:2412.12327, 2024
12024
On the Benefits of Attribute-Driven Graph Domain Adaptation
R Fang, B Li, Z Kang, Q Zeng, R Pu, NH Dashtbayaz, B Wang, C Ling
arXiv preprint arXiv:2502.06808, 2025
2025
Fedelr: When Federated Learning Meets Learning with Noisy Labels
R Pu, L Yu, S Zhan, G Xu, F Zhou, CX Ling, B Wang
Available at SSRN 4995227, 0
Directional Domain Generalization
W Wang, J Li, R Pu, G Xu, F Zhou, C Shui, C Ling, B Wang
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