School of Computer Science and Engineering, College of Software Engineering, Southeast University

Pattern Learning and Mining (PALM) Lab

Correspondence

Mail: School of Computer Science and Engineering, Jiulonghu Campus, Southeast University, Nanjing 211189, China

office: 506, Computer Science Building, Jiulonghu Campus, Southeast University

Email: xning AT seu.edu.cn

招收 2025年 秋季入学硕士研究生（计算机学院、软件学院），欢迎联系！

Biogeraphy

Currently, I am an associate professor at the PALM Group, School of Computer Science and Engineering, Southeast University.

I received my B.Sc. degree from University of Science and Technology of China, M.Sc. degree from University of Chinese Academy of Sciences, and Ph.D. degree (supervisor Prof. Xin Geng) from Southeast University.

Research Interests

My research interests include machine learning and data mining.

Selected Publications

Journal Articles

• N. Xu, J. Shu, R.-Y. Zheng, X. Geng, D. Meng, M.-L. Zhang. Variational Label Enhancement. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2023, 45(5): 6537-6551. (CCF-A)
• N. Xu, C. Qiao, Y. Zhao, X. Geng, M.-L. Zhang. Variational Label Enhancement for Instance-Dependent Partial Label Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2024, in press. (CCF-A)
• J. Lv, B. Liu, L. Feng, N. Xu, M. Xu, B. An, G. Niu, X. Geng, M. Sugiyama. On the Robustness of Average Losses for Partial-Label Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2024, 46 (5), 2569-2583. (CCF-A)
• N. Xu, Y.-D. Wu, C. Qiao, Y. Ren, M. Zhang, X. Geng. Multi-View Partial Multi-Label Learning via Graph-Fusion-Based Label Enhancement. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023, 35(11): 11656-11667. (CCF-A)
• N. Xu, Y.-P. Liu, and X. Geng. Label Enhancement for Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021, 33(4): 1632-1643. (CCF-A)
• 耿新, 徐宁. 标记分布学习与标记增强. 中国科学: 信息科学, 2018, 48(5): 521-530.

Conference Papers

• N. Xu, Y. Hu, C. Qiao, X. Geng. Aligned Objective for Soft-Pseudo-Label Generation in Supervised Learning. In: Proceedings of the International Conference on Machine Learning (ICML'24), Vienna, Austria, 2024, 55033-55047. (CCF-A)
• Y. Liu, J. Lv, X. Geng, N. Xu. Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency. In: Proceedings of the International Conference on Machine Learning (ICML'24), Vienna, Austria, 2024, 31614-31628. (CCF-A)
• B. Liu, N. Xu, J. Lv, X. Geng. Revisiting Pseudo-Label for Single-Positive Multi-Label Learning. In: Proceedings of the International Conference on Machine Learning (ICML'23), Honolulu, Hawaii, 2023, 22249-22265. (CCF-A)
• C. Qiao, N. Xu, J. Lv, Y. Ren, X. Geng. FREDIS: A Fusion Framework of Refinement and Disambiguation for Unreliable Partial Label Learning. In: Proceedings of the International Conference on Machine Learning (ICML'23), Honolulu, Hawaii, 2023, 28321-28336. (CCF-A)
• N. Xu, B. Liu, J. Lv, C. Qiao, X. Geng. Progressive Purification for Instance-Dependent Partial Label Learning. In: Proceedings of the International Conference on Machine Learning (ICML'23), Honolulu, Hawaii, 2023, 38551-38565. (CCF-A)
• C. Qiao, N. Xu, X. Geng. Decompositional Generation Process for Instance-Dependent Partial Label Learning. In: Proceedings of the International Conference on Learning Representations (ICLR'23), Kigali, Rwanda, 2023. (Spotlight)
• N. Xu, C. Qiao, J. Lv, X. Geng, M.-L. Zhang. One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), New Orleans, LA, 2022, 21765-21776. (CCF-A, Oral)
• N. Xu, C. Qiao, X. Geng, M.-L. Zhang. Instance-Dependent Partial Label Learning. In: Advances in Neural Information Processing Systems 34 (NeurIPS'21), Virtual Conference, 2021, 27119-27130. (CCF-A, Spotlight)
• N. Xu, J. Shu, Y.-P. Liu, X. Geng. Variational Label Enhancement. In: Proceedings of the International Conference on Machine Learning (ICML'20), Vienna, Austria, 2020, 10597-10606. (CCF-A)
• N. Xu, A. Tao and X. Geng. Label Enhancement for Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 2926-2932. (CCF-A)

Awards

• Young Elite Scientists Sponsorship Program of Jiangsu Association for Science and Technology, 2022.
• Outstanding Doctoral Dissertation Award of CCF, 2021.
• Outstanding Doctoral Dissertation Award of Jiangsu Province, 2021.
• Outstanding Doctoral Dissertation Award of Jiangsu Computer Society, 2021.
• Deutscher Akademischer Austauschdienst AInet Award, 2020.

Students

• 2020: Cong-Yu Qiao (乔聪玉) [co-supervison with Prof. Xin Geng]: CCF-A类论文7篇.
• 2021: Jia-Yu Li (李加羽): CCF-B类论文1篇.
• 2021: Yong-Di Wu (吴永迪): CCF-A类论文1篇.
• 2021: Biao Liu (刘彪) [co-supervison with Prof. Xin Geng]: CCF-A类论文4篇.
• 2022: Yangfan Liu (刘杨帆) : CCF-A类论文1篇.
• 2023: Yihao Hu (胡益豪) : CCF-A类论文1篇.
• 2023: Yuchen Zhao (赵宇晨) : CCF-A类论文1篇.