Hui Xue

Hui Xue

薛    晖

Ph.D., Professor
Head of the Department of Computer Science,
School of Computer Science and Engineering
Executive Deputy Director of AIIA Lab
Pattern Learning and Mining (PALM) Lab
Southeast University
PALM Lab
SEU

Correspondence

Mail: School of Computer Science and Engineering,
Jiulonghu Campus, Southeast University,
Nanjing 211189, China
Office: 512, Computer Science Building,
Jiulonghu Campus, Southeast University
Nanjing 211189, China
Email: hxue@seu.edu.cn

Brief Introduction | Recruitment | News | Selected Publications | Courses | Codes & Data

Brief Introduction

My research interests mainly include machine learning and pattern recognition. Currently, I am a professor at the PALM Group, School of Computer Science and Engineering, Southeast University. I received my B.Sc. degree in mathematics from Nanjing Normal University in 2002, and M.Sc. degree in mathematics from Nanjing University of Aeronautics & Astronautics (NUAA) in 2005. In 2008, I received my Ph.D. degree in computer science also from NUAA. I was also a member of PARNEC group led by my supervisor Prof. Songcan Chen.
Research Interest

Recruitment

Looking for highly self-motivated students aiming to enroll in the MSc. and PhD. programs.
欢迎计划申请2025级博士生、直博生、硕士生的同学与我邮件联系.

News

[2024.05.02] One paper is accepted by ICML`24.
[2024.04.02] One paper is accepted by TNNLS.
[2023.12.09] One paper is accepted by AAAI`24.
[2023.09.22] One paper is accepted by NeurIPS`23.
[2023.04.20] Three papers are accepted by IJCAI`23.
[2023.02.05] One paper is accepted by TPAMI.

Selected Publications

  * denotes corresponding author.

Conference Papers


  1. Jinyue Tian, Hui Xue*, Yanfang Xue, Pengfei Fang. Copula-Nested Spectral Kernel Network. In: Proceedings of the 41st International Conference on Machine Learning (ICML'24), Vienna, Austria, in press, 2024. [PDF]

  2. Shipeng Zhu, Pengfei Fang, Chenjie Zhu, Zuoyan Zhao, Qiang Xu, Hui Xue*. Text Image Inpainting via Global Structure-Guided Diffusion Models. In: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 38(7): 7775-7783, Vancouver, Canada, 2024. [PDF]

  3. Yangfang Xue, Pengfei Fang, Jinyue Tian, Shipeng Zhu, Hui Xue*. CosNet: A Generalized Spectral Kernel Network. In: Advances in Neural Information Processing Systems (NeurIPS'23), 36: 37273-37285, New Orleans, USA, 2023. [PDF]

  4. Meimei Yang, Pengfei Fang, Hui Xue*. Expanding the Hyperbolic Kernels: A Curvature-aware Isometric Embedding View. In: Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), 4469-4477, Macao, China, 2023. [PDF]

  5. Yuexuan An, Xingyu Zhao, Hui Xue*. Learning to Learn from Corrupted Data for Few-Shot Learning. In: Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), 3423-3431, Macao, China, 2023. [PDF]

  6. Yongjuan Che, Yuexuan An, Hui Xue*. Boosting Few-Shot Open-Set Recognition with Multi-Relation Margin Loss. In: Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), 3505-3513, Macao, China, 2023. [PDF]

  7. Shipeng Zhu, Zuoyan Zhao, Pengfei Fang, Hui Xue*. Improving Scene Text Image Super-resolution via Dual Prior Modulation Network. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI'23), 37(3): 3843-3851, Washington DC, USA, 2023. [PDF]

  8. Zheng-Fan Wu, Yi-Nan Feng, Hui Xue*. Automatically Gating Multi-Frequency Patterns through Rectified Continuous Bernoulli Units with Theoretical Principles. In: Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI'22), 3594-3600, Vienna, Austria, 2022. [PDF]

  9. Yuexuan An, Hui Xue*, Xingyu Zhao, Lu Zhang. Conditional Self-Supervised Learning for Few-Shot Classification. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21), 2140-2146, Montreal, Quebec, Canada, 2021. [PDF]

  10. Zheng-Fan Wu, Hui Xue*, Weimin Bai. Learning Deeper Non-monotonic Networks by Softly Transferring Solution Space. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21), 3200-3206, Montreal, Quebec, Canada, 2021. [PDF]

  11. Qiao Liu, Hui Xue*. Adversarial Spectral Kernel Matching for Unsupervised Time Series Domain Adaption. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21), 2744-2750, Montreal, Quebec, Canada, 2021. [PDF]

  12. Hui Xue*, Zheng-Fan Wu. BaKer-Nets: Bayesian Random Kernel Mapping Networks. In: Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI'20), 3073-3079, Yokohama, Japan, 2020. [PDF]

  13. Hui Xue*, Xin-Kai Sun, Wei-Xiang Sun. Multi-hop Hierarchical Graph Neural Networks. In: Proceedings of the 7th IEEE International Conference on Big Data and Smart Computing (BigComp'20), 82-89, 2020. [PDF]

  14. Hui Xue*, Zheng-Fan Wu, Wei-Xiang Sun. Deep Spectral Kernel Learning. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19), 4019-4025, Macao, China, 2019. [PDF]

  15. Fa Zheng, Hui Xue*. Subclass Maximum Margin Tree Error Correcting Output Codes. In: Proceedings of the 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI'18), LNAI 11012, 454-462, Nanjing, China, 2018. [PDF]

  16. Hui Xue*, Yu Song, Hai-Ming Xu. Multiple Indefinite Kernel Learning for Feature Selection. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), 3210-3216, Melbourne, Australia, 2017. [PDF]

  17. Hai-Ming Xu, Hui Xue*, Xiao-Hong Chen, Yun-Yun Wang. Solving Indefinite Kernel Support Vector Machine with Difference of Convex Functions Programming. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17),2782-2788, San Francisco, California, USA, 2017. [PDF]

  18. Fa Zheng, Hui Xue*, Xiaohong Chen, Yunyun Wang. Maximum Margin Tree Error Correcting Output Codes. In: Proceedings of the 14th Pacific Rim International Conference on Artificial Intelligence (PRICAI'16), LNAI 9810, 681-691, Phuket, Thailand, 2016. [PDF]

  19. Chao Xing, Xin Geng, Hui Xue. Logistic Boosting Regression for Label Distribution Learning. In: Proceedings of the 26th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'16), 4489-4497, Las Vegas, Nevada, USA, 2016. [PDF]

  20. Yin Zhou, Hui Xue, Xin Geng. Emotion Distribution Recognition from Facial Expressions. In: Proceedings of the 23rd ACM International Conference on Multimedia (ACM MM'15), 1247-1250, Brisbane, Australia, 2015. [PDF]

  21. Dayin Zhang, Hui Xue*. Lp-norm Multiple Kernel Learning with Diversity of Classes. In: Proceedings of the 13rd Pacific Rim Knowledge Acquisition Workshop (PKAW'14), 38-47, Gold Coast, Australia, 2014. [PDF]

  22. Hui Xue*, Songcan Chen, Jijian Huang. Discriminative Indefinite Kernel Classifier from Pairwise Constraints and Unlabeled Data. In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR'12), 497-500, Tsukuba, Japan, 2012. [PDF]

  23. Jijian Huang, Hui Xue*, Yuqing Zhai. Semi-supervised Discriminatively Regularized Classifier with Pairwise Constraints. In: Proceedings of the 12th Pacific Rim International Conference on Artificial Intelligence (PRICAI'12), LNAI 7458, 112-123, Kuching, Sarawak, Malaysia, 2012. [PDF]

  24. Hui Xue, Songcan Chen, Qiang Yang. Structural Support Vector Machine. In: Proceedings of the 15th International Symposium on Neural Networks (ISNN'08), Part I, LNCS5263, 501-511, 2008. [PDF]

  25. Hui Xue, Songcan Chen. Alternative Robust Local Embedding. In: Proceedings of the 1st International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR'07), 591-596, 2007. [PDF]

Journal Papers


  1. Yuexuan An, Hui Xue*, Xingyu Zhao, Ning Xu, Pengfei Fang, Xin Geng. Leveraging Bilateral Correlations for Multi-Label Few-Shot Learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS'24), in press, 2024. [PDF]

  2. Yuexuan An, Hui Xue*, Xingyu Zhao, Jing Wang. From Instance to Metric Calibration: A Unified Framework for Open-World Few-Shot Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI'23), 45(8): 9757-9773, 2023. [PDF]

  3. Meimei Yang, Qiao Liu, Xinkai Sun, Na Shi, Hui Xue*. Towards Kernelizing the Classifier for Hyperbolic Data. Frontiers of Computer Science (FCS'24), 18(1), 2024.

  4. Qipeng Zhu, Zhuoyan Luo, Shipeng Zhu, Qi Jing, Zihang Xu, Hui Xue*. FATE: A Three-stage Method for Arithmetical Exercise Correction. Neural Computing and Applications (NCA'23), 35: 23491-23506, 2023. [PDF]

  5. Jing Wang, Xin Geng, Hui Xue. Re-weighting Large Margin Label Distribution Learning for Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI'22), 44(9): 5445-5459, 2022. [PDF]

  6. Yuexuan An, Hui Xue*. Indefinite Twin Support Vector Machine with DC Functions Programming. Pattern Recognition (PR'22), 121, 2022. [PDF]

  7. Qing Tian, Chuang Ma, Fengyuan Zhang, Shun Peng, Hui Xue. Source-free Unsupervised Domain Adaption with Sample Transport Learning. Journal of Computer Science and Technology (JCST'21), 36(3): 606-616, 2021. [PDF]

  8. Weixiang Sun, Hui Xue*. Learning Graph-level Representation from Local-structural Distribution with Graph Neural Networks. Knowledge-Based Systems (KBS'21), 230, 2021. [PDF]

  9. Jun Jiao, Hui Xue*, Jundi Ding. Non-local Duplicate Pooling Network for Salient Object Detection. Applied Intelligence (Appl Intell'21), 51: 6881-6894, 2021. [PDF]

  10. Hui Xue*, Yu Song, Haiming Xu. Multiple Indefinite Kernel Learning for Feature Selection. Knowledge-Based Systems (KBS'20), 191(5), 2020. [PDF]

  11. Hui Xue*, Zhen Ren. Sketch Discriminatively Regularized Online Gradient Descent Classification. Applied Intelligence (Appl Intell'20), 50: 1367-1378, 2020. [PDF]

  12. Hui Xue*, Yu Song. Non-convex Approximation based l0-norm Multiple Indefinite Kernel Feature Selection. Applied Intelligence (Appl Intell'20), 50: 192-202, 2020. [PDF]

  13. Hui Xue*, Haiming Xu, Xiaohong Chen, Yunyun Wang. A Primal Perspective for Indefinite Kernel SVM Problem. Frontiers of Computer Science (FCS'20), 14(2): 349-363, 2020. [PDF]

  14. Hui Xue*, Lin Wang, Songcan Chen, Yunyun Wang. A Primal Framework for Indefinite Kernel Learning. Neural Processing Letters (NPL'19), 50: 165-188, 2019. [PDF]

  15. Hui Xue*, Sen Li, Xiaohong Chen, Yunyun Wang. A Maximum Margin Clustering Algorithm based on Indefinite Kernels. Frontiers of Computer Science (FCS'19), 13(4), 813-827, 2019. [PDF]

  16. Yunyun Wang, Yan Meng, Yun Li, Songcan Chen, Zhenyong Fu, Hui Xue*. Semi-superivsed Manifold Regularization with Adaptive Graph Construction. Pattern Recognition Letters (PRL'17), 98(15), 90-95, 2017. [PDF]

  17. Yunyun Wang, Yan Meng, Zhengyong Fu, Hui Xue. Towards Safe Semi-supervised Classification: Adjusted Cluster Assumption via Clustering. Neural Processing Letters (NPL'17), 46(3): 1031-1042, 2017. [PDF]

  18. Qing Tian, Hui Xue, Lishan Qiao. Human Age Estimation by Considering both the Ordinality and Similarity of Ages. Neural Processing Letters (NPL'16), 43: 505-521, 2016. [PDF]

  19. Mingxia Liu, Daoqiang Zhang, Songcan Chen, Hui Xue. Joint Binary Classifier Learning for ECOC-based Multi-class Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI'16), 38(11): 2335-2341, 2016. [PDF]

  20. Yunyun Wang, Songcan Chen, Hui Xue* , Zhenyong Fu. Semi-supervised Classification Learning by Discrimination-aware Manifold Regularization. Neurocomputing (Neurocomp'15), 147: 299-306, 2015. [PDF]

  21. Jun Xie, Lu Yu, Lei Zhu, Hui Xue . Boosting Decision Stumps to Do Pairwise Classification. Electronics Letters (EL'14), 50(12): 866-867, 2014. [PDF]

  22. Hui Xue*, Songcan Chen. Discriminality-driven Regularization Framework for Indefinite Kernel Machine. Neurocomputing (Neurocomp'14), 133: 209-221, 2014. [PDF]

  23. Hui Xue*, Songcan Chen. Orthogonality-based Label Correction in Multi-class Classification . Electronics Letters (EL'13), 49(12): 754-755, 2013. [PDF]

  24. Xiaohong Chen, Songcan Chen, Hui Xue. Universum Linear Discriminant Analysis. Electronics Letters (EL'12), 48(22): 1407-1408, 2012. [PDF]

  25. Yunyun Wang, Songcan Chen, Hui Xue. Can Under-exploited Structure of Original-classes Help ECOC-based Multi-class Classification? Neurocomputing (Neurocomp'12), 89: 158-167, 2012. [PDF]

  26. Xiaohong Chen, Songcan Chen, Hui Xue, Xudong Zhou. A Unified Dimensionality Reduction Framework for semi-paired and semi-supervised multi-view data. Pattern Recognition (PR'12), 45(5): 2005-2018, 2012. [PDF]

  27. Xiaohong Chen, Songcan Chen, Hui Xue. Large Correlation Analysis. Applied Mathematics and Computation (AMC'11). 217(22): 9041-9052, 2011. [PDF]

  28. Hui Xue, Songcan Chen, Qiang Yang. Structural Regularized Support Vector Machine: A Framework for Structural Large Margin Classifier. IEEE Transactions on Neural Networks (TNN'11), 22(4): 573-587, 2011. [PDF]

  29. Hui Xue, Songcan Chen. Glocalization Pursuit Support Vector Machine. Neural Computing and Applications (NCA'11), 20(7): 1043-1053, 2011. [PDF]

  30. Yunyun Wang, Songcan Chen, Hui Xue. Support Vector Machines Incorporated with Feature Discrimination. Expert Systems with Applications (ESA'11), 38: 12506-12513, 2011. [PDF]

  31. Yunyun Wang, Songcan Chen, Hui Xue. Structure-embedded AUC-SVM. International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI'10), 24(5): 667-690, 2010. [PDF]

  32. Zhe Wang, Songcan Chen, Hui Xue, Zhisong Pan. A Novel Regularization Learning for Single-view Patterns: Multi-view Discriminative Regularization. Neural Processing Letters (NPL'10), 31(3): 159-175, 2010. [PDF]

  33. Hui Xue, Songcan Chen, Qiang Yang. Discriminatively Regularized Least-squares Classification. Pattern Recognition (PR'09), 42(1): 93-104, 2009. [PDF]

  34. Hui Xue, Yulian Zhu, Songcan Chen. Local Ridge Regression for Face Recognition. Neurocomputing (Neurocomp'09), 72: 1342-1346, 2009. [PDF]

  35. Hui Xue, Songcan Chen, Qiang Yang. Discriminative Regularization: A New Classifier Learning Method. Transactions of Nanjing University of Aeronautics & Astronautics (TNUAA'09), 26(1): 65-74, 2009. [PDF]

  36. Hui Xue, Qiang Yang, Songcan Chen. Support Vector Machines. The Top Ten Algorithms in Data Mining, 37-59, Chapman & Hall/CRC, Data Mining and Knowledge Discovery Series, Taylor and Francis Group, 2009. [PDF]

  37. Hui Xue, Songcan Chen, Xiaoqin Zeng. Classifier Learning with A New Locality Regularization Method. Pattern Recognition (PR'08), 41(5): 1479-1490, 2008. [PDF]

Courses

1. Discrete Mathematics [打包下载]

Time: Spring Semester
To: Undergraduate students
Book: 屈婉玲, 耿素云, 张立昂. 离散数学, 高等教育出版社, 2008
Slides: Ch1 Ch2 Ch3 Ch4 Ch5 Ch6 Ch7 Ch8 Ch9 Ch10 Ch11 Ch12 Ch13 Ch14 Ch15 Ch16

2. Pattern Recognition [打包下载]

Time: Autumn Semester
To: Graduate students
Book: Richard O.Duda, Peter E.Hart, David G.Stork. Pattern Classification 2nd Edition, John Wiley & sons, 2004
Slides: Ch1 Ch2 Ch3 Ch4 Ch5 Ch6 Ch7 Ch8 Ch9 Ch10

Codes & Data