Publications

2025

1. TPAMI

   

   Unraveling the Mysteries of Label Noise in Source-Free Domain Adaptation: Theory and Practice

   Gezheng Xu^*, Li Yi^*, Pengcheng Xu, Jiaqi Li, Ruizhi Pu, Changjian Shui, Charles Ling, A. Ian McLeod, and Boyu Wang

   IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

   DOI Bib Code

   @article{xu2025unraveling,
     author = {Xu, Gezheng and Yi, Li and Xu, Pengcheng and Li, Jiaqi and Pu, Ruizhi and Shui, Changjian and Ling, Charles and McLeod, A. Ian and Wang, Boyu},
     journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
     title = {Unraveling the Mysteries of Label Noise in Source-Free Domain Adaptation: Theory and Practice},
     year = {2025},
     doi = {10.1109/TPAMI.2025.3536845},
   }

2. ICLR

   

   Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control

   Gezheng Xu^*, Hui Guo^*, Li Yi, Charles Ling, Boyu Wang, and Grace Yi

   In International Conference on Learning Representations (ICLR), 2025

   Bib Code

   @inproceedings{xu2025revisiting,
     title = {Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control},
     author = {Xu, Gezheng and Guo, Hui and Yi, Li and Ling, Charles and Wang, Boyu and Yi, Grace},
     booktitle = {International Conference on Learning Representations (ICLR)},
     year = {2025},
   }

3. ICLR

   

   ZETA: Leveraging Z-order Curves for Efficient Top-k Attention

   Qiuhao Zeng, Jerry Huang, Peng Lu, Gezheng Xu, Boxing Chen, Charles Ling, and Boyu Wang

   International Conference on Learning Representations (ICLR), 2025

   Bib

   @article{zeng2025zeta,
     author = {Zeng, Qiuhao and Huang, Jerry and Lu, Peng and Xu, Gezheng and Chen, Boxing and Ling, Charles and Wang, Boyu},
     title = {ZETA: Leveraging Z-order Curves for Efficient Top-k Attention},
     journal = {International Conference on Learning Representations (ICLR)},
     year = {2025},
   }

4. AAAI

   

   Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced Regression

   Ruizhi Pu, Gezheng Xu, Ruiyi Fang, Binkun Bao, Charles X Ling, and Boyu Wang

   AAAI Conference on Artificial Intelligence (AAAI), 2025

   Bib

   @article{pu2024leveraging,
     author = {Pu, Ruizhi and Xu, Gezheng and Fang, Ruiyi and Bao, Binkun and Ling, Charles X and Wang, Boyu},
     title = {Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced Regression},
     journal = {AAAI Conference on Artificial Intelligence (AAAI)},
     year = {2025},
   }

2024

1. ICML

   

   Intersectional Unfairness Discovery

   Gezheng Xu, Qi Chen, Charles Ling, Boyu Wang, and Changjian Shui

   In International Conference on Machine Learning (ICML), 2024

   Bib HTML PDF Code Poster

   @inproceedings{pmlr-v235-xu24d,
     title = {Intersectional Unfairness Discovery},
     author = {Xu, Gezheng and Chen, Qi and Ling, Charles and Wang, Boyu and Shui, Changjian},
     booktitle = {International Conference on Machine Learning (ICML)},
     pages = {54888--54917},
     year = {2024},
     editor = {Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix},
     volume = {235},
     series = {Proceedings of Machine Learning Research},
     publisher = {PMLR},
   }

2. AAAI

   

   Generalizing across Temporal Domains with Koopman Operators

   Qiuhao Zeng, Wei Wang, Fan Zhou, Gezheng Xu, Ruizhi Pu, Changjian Shui, Christian Gagné, Shichun Yang, Charles X. Ling, and Boyu Wang

   In AAAI Conference on Artificial Intelligence (AAAI), 2024

   Bib HTML

   @inproceedings{DBLP:conf/aaai/Zeng00XPS0YLW24,
     author = {Zeng, Qiuhao and Wang, Wei and Zhou, Fan and Xu, Gezheng and Pu, Ruizhi and Shui, Changjian and Gagn{\'{e}}, Christian and Yang, Shichun and Ling, Charles X. and Wang, Boyu},
     title = {Generalizing across Temporal Domains with Koopman Operators},
     booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
     pages = {16651--16659},
     year = {2024},
   }

2023

1. ICLR

   

   When Source-Free Domain Adaptation Meets Learning with Noisy Labels

   Li Yi^*, Gezheng Xu^*, Pengcheng Xu, Jiaqi Li, Ruizhi Pu, Charles Ling, A Ian McLeod, and Boyu Wang

   International Conference on Learning Representations (ICLR), 2023

   Bib Video Code Slides

   @article{yi2023source,
     title = {When Source-Free Domain Adaptation Meets Learning with Noisy Labels},
     author = {Yi, Li and Xu, Gezheng and Xu, Pengcheng and Li, Jiaqi and Pu, Ruizhi and Ling, Charles and McLeod, A Ian and Wang, Boyu},
     journal = {International Conference on Learning Representations (ICLR)},
     year = {2023},
   }

2. KBS

   

   Label Shift Conditioned Hybrid Querying for Deep Active Learning

   Jiaqi Li, Haojia Kong, Gezheng Xu, Changjian Shui, Ruizhi Pu, Zhao Kang, Charles X Ling, and Boyu Wang

   Knowledge-Based Systems, 2023

   Bib

   @article{li2023label,
     title = {Label Shift Conditioned Hybrid Querying for Deep Active Learning},
     author = {Li, Jiaqi and Kong, Haojia and Xu, Gezheng and Shui, Changjian and Pu, Ruizhi and Kang, Zhao and Ling, Charles X and Wang, Boyu},
     journal = {Knowledge-Based Systems},
     volume = {274},
     pages = {110616},
     year = {2023},
     publisher = {Elsevier},
   }

3. TKDE

   

   Towards more General Loss and Setting in Unsupervised Domain Adaptation

   Changjian Shui^*, Ruizhi Pu^*, Gezheng Xu, Jun Wen, Fan Zhou, Christian Gagné, Charles X Ling, and Boyu Wang

   IEEE Transactions on Knowledge and Data Engineering, 2023

   Bib

   @article{shui2023towards,
     title = {Towards more General Loss and Setting in Unsupervised Domain Adaptation},
     author = {Shui, Changjian and Pu, Ruizhi and Xu, Gezheng and Wen, Jun and Zhou, Fan and Gagn{\'e}, Christian and Ling, Charles X and Wang, Boyu},
     journal = {IEEE Transactions on Knowledge and Data Engineering},
     volume = {35},
     number = {10},
     pages = {10140--10150},
     year = {2023},
     publisher = {IEEE},
   }

4. JMLR

   

   Gap Minimization for Knowledge Sharing and Transfer

   Boyu Wang, Jorge A Mendez, Changjian Shui, Fan Zhou, Di Wu, Gezheng Xu, Christian Gagné, and Eric Eaton

   Journal of Machine Learning Research, 2023

   Bib

   @article{wang2023gap,
     title = {Gap Minimization for Knowledge Sharing and Transfer},
     author = {Wang, Boyu and Mendez, Jorge A and Shui, Changjian and Zhou, Fan and Wu, Di and Xu, Gezheng and Gagn{\'e}, Christian and Eaton, Eric},
     journal = {Journal of Machine Learning Research},
     volume = {24},
     number = {33},
     pages = {1--57},
     year = {2023},
   }

2022

1. NeurIPS

   

   On Learning Fairness and Accuracy on Multiple Subgroups

   Changjian Shui^*, Gezheng Xu^*, Qi Chen, Jiaqi Li, Charles X Ling, Tal Arbel, Boyu Wang, and Christian Gagné

   Advances in Neural Information Processing Systems (NeurIPS), 2022

   Bib HTML Code

   @article{shui2022learning,
     title = {On Learning Fairness and Accuracy on Multiple Subgroups},
     author = {Shui, Changjian and Xu, Gezheng and Chen, Qi and Li, Jiaqi and Ling, Charles X and Arbel, Tal and Wang, Boyu and Gagn{\'e}, Christian},
     journal = {Advances in Neural Information Processing Systems (NeurIPS)},
     volume = {35},
     pages = {34121--34135},
     year = {2022},
   }

2021

1. BMC Bioinformatics

   

   External Features Enriched Model for Biomedical Question Answering

   Gezheng Xu, Wenge Rong, Yanmeng Wang, Yuanxin Ouyang, and Zhang Xiong

   BMC Bioinformatics, 2021

   Bib Code

   @article{xu2021external,
     title = {External Features Enriched Model for Biomedical Question Answering},
     author = {Xu, Gezheng and Rong, Wenge and Wang, Yanmeng and Ouyang, Yuanxin and Xiong, Zhang},
     journal = {BMC Bioinformatics},
     volume = {22},
     number = {1},
     pages = {272},
     year = {2021},
     publisher = {Springer},
   }