Gezheng Xu

According to our database, Gezheng Xu authored at least 17 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

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, A. Ian McLeod, Boyu Wang, Charles Ling

IEEE Trans. Pattern Anal. Mach. Intell., May, 2025

Homophily Enhanced Graph Domain Adaptation.

Ruiyi Fang, Bingheng Li, Jingyu Zhao, Ruizhi Pu, Qiuhao Zeng, Gezheng Xu, Charles Ling, Boyu Wang

CoRR, May, 2025

Uniform Noise Distribution and Compact Clusters: Unveiling the Success of Self-Supervised Learning in Label Noise.

Pengcheng Xu, Li Yi, Gezheng Xu, Xi Chen, A. Ian McLeod, Charles Ling, Boyu Wang

Trans. Mach. Learn. Res., 2025

FedELR: When federated learning meets learning with noisy labels.

Ruizhi Pu, Lixing Yu, Shaojie Zhan, Gezheng Xu, Fan Zhou, Charles X. Ling, Boyu Wang

Neural Networks, 2025

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

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced Regression.

Ruizhi Pu, Gezheng Xu, Ruiyi Fang, Bingkun Bao, Charles Ling, Boyu Wang

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced Regression.

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

CoRR, 2024

Intersectional Unfairness Discovery.

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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, Boyu Wang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

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, Boyu Wang

IEEE Trans. Knowl. Data Eng., October, 2023

Label shift conditioned hybrid querying for deep active learning.

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

Knowl. Based Syst., 2023

Gap Minimization for Knowledge Sharing and Transfer.

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

J. Mach. Learn. Res., 2023

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, Boyu Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Evolving Domain Generalization.

William Wei Wang, Gezheng Xu, Ruizhi Pu, Jiaqi Li, Fan Zhou, Changjian Shui, Charles X. Ling, Christian Gagné, Boyu Wang

CoRR, 2022

On Learning Fairness and Accuracy on Multiple Subgroups.

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

External features enriched model for biomedical question answering.

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

BMC Bioinform., 2021