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Correspondence

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

Office: 512, Computer Science Building, 
            Jiulonghu Campus, Southeast University
 

 

Hui Xue
薛   晖

Ph.D.,Professor

Pattern Learning and Mining (PALM) Lab

School of Computer Science and Engineering

Southeast University


Email: hxue@seu.edu.cn
 
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Brief Introduction | Selected Publications | Courses | Codes & Data
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Brief Introduction

 

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Selected Publications

Conference Papers

  1. Yuexuan An, Hui Xue, Xinyu Zhao, Lu Zhang. Conditional self-supervised learning for few-shot classification. In: Proceedings of 30th International Joint Conference on Artificial Intelligence (IJCAI), Montreal, Quebec, Canada, 2021.[PDF]
  2. Zhengfan Wu, Hui Xue, Weimin Bai. Learning deeper non-monotonic networks by softly transferring solution space. In: Proceedings of 30th International Joint Conference on Artificial Intelligence (IJCAI), Montreal, Quebec, Canada, 2021.[PDF]
  3. Qiao Liu, Hui Xue. Adversarial spectral kernel matching for unsupervised time series domain adaption. In: Proceedings of 30th International Joint Conference on Artificial Intelligence (IJCAI), Montreal, Quebec, Canada, 2021.[PDF]
  4. Hui Xue, Zhengfan Wu. BaKer-Nets: Bayesian Random Kernel Mapping Networks. Proceedings of 29th International Joint Conference on Artificial Intelligence (IJCAI), 3073-3079, Yokohama, Japan, 2020.[PDF]

  5. Hui Xue, Xinkai Sun, Weixiang Sun. Multi-hop hierarchical graph neural networks. Proceedings of IEEE International Conference on Big Data and Smart Computing (BigComp), 82-89, 2020.[PDF]
  6. Hui Xue, Zheng-Fan Wu, Wei-Xiang Sun. Deep Spectral Kernel Learning. International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, 2019.[PDF]
  7. Fa Zheng, Hui Xue. Subclass Maximum Margin Tree Error Correcting Output Codes. Proceedings of Pacific Rim International Conference on Artificial Intelligence (PRICAI), LNAI 11012, 454-462, Nanjing, China, 2018.[PDF]
  8. Hui Xue, Yu Song, Haiming Xu. Multiple Indefinite Kernel Learning for Feature Selection. International Joint Conference on Artificial Intelligence (IJCAI),2017.[PDF]
  9. Haiming Xu, Hui Xue, Xiaohong Chen, Yunyun Wang. Solving indefinite kernel support vector machine with difference of convex functions programming. Proceedings of 31th AAAI Conference on Artificial Intelligence (AAAI),San Francisco,California,USA,2017.[PDF]
  10. Fa Zheng, Hui Xue, Xiaohong Chen, Yunyun Wang. Maximum margin tree error correcting output codes. Proceedings of 14th Pacific Rim International Conference on Artificial Intelligence (PRICAI), LNAI 9810, 681-691, Phuket, Thailand, 2016.[PDF]
  11. Chao Xing, Xin Geng, Hui Xue. Logistic boosting regression for label distribution learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 4489-4497, Las Vegas, Nevada, USA, 2016.[PDF]
  12. Yin Zhou, Hui Xue, Xin Geng. Emotion distribution recognition from facial expressions. Proceedings of 23rd ACM International Conference on Multimedia (ACM MM), 1247-1250, Brisbane, Australia, 2015.[PDF]
  13. Dayin Zhang, Hui Xue. Lp-norm multiple kernel learning with diversity of classes. Pacific Rim Knowledge Acquisition Workshop (PKAW), 38-47, Gold Coast, Australia, 2014.[PDF]
  14. Hui Xue, Songcan Chen, Jijian Huang. Discriminative indefinite kernel classifier from pairwise constraints and unlabeled data. Proceedings of 21st International Conference on Pattern Recognition (ICPR), 497-500, Tsukuba, Japan, 2012.[PDF]
  15. Jijian Huang, Hui Xue, Yuqing Zhai. Semi-supervised discriminatively regularized classifier with pairwise constraints. Proceedings of 12th Pacific Rim International Conference on Artificial Intelligence (PRICAI), LNAI 7458, 112-123, Kuching, Sarawak, Malaysia, 2012.[PDF]
  16. Hui Xue, Songcan Chen, Qiang Yang. Structural support vector machine. Proceedings of 15th International Symposium on Neural Networks (ISNN), Part I, LNCS5263, 501-511, 2008.[PDF]
  17. Hui Xue, Songcan Chen. Alternative robust local embedding. Proceedings of International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), 591-596, 2007.[PDF]

Journal Papers

  1. Jing Wang, Xin Geng, Hui Xue. Re-weighting large margin label distribution learning for classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 [PDF]
  2. Yuexuan An, Hui Xue. Indefinite twin support vector machine with DC functions programming. Pattern Recognition, 2022 [PDF]
  3. 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, 36(3): 606-616, 2021
  4. Weixiang Sun, Hui Xue. Learning graph-level representation from local-structural distribution with graph neural networks. Knowledge-Based Systems, 2021 [PDF]
  5. Jun Jiao, Hui Xue, Jundi Ding. Non-local duplicate pooling network for salient object detection. Applied Intelligence, 2021
  6. Hui Xue, Yu Song, Haiming Xu. Multiple indefinite kernel learning for feature selection. Knowledge-Based Systems, 191, 2020, DOI: 10.1016/j.knosys.2019.105272 [PDF]
  7. Hui Xue, Zhen Ren. Sketch discriminatively regularized online gradient descent classification. Applied Intelligence, 50:13671378, 2020. [PDF]
  8. Hui Xue, Yu Song. Non-convex approximation based l0-norm multiple indefinite kernel feature selection. Applied Intelligence, 50:192202, 2020.[PDF]
  9. Hui Xue, Haiming Xu, Xiaohong Chen, Yunyun Wang. A primal perspective for indefinite kernel SVM problem. Frontiers of Computer Science, 14:349363, 2020.
  10. Hui Xue, Lin Wang, Songcan Chen, Yunyun Wang. A primal framework for indefinite kernel learning. Neural Processing Letters, 50(1): 165-188, 2019.[PDF]
  11. Hui Xue, Sen Li, Xiaohong Chen, Yunyun Wang. A maximum margin clustering algorithm based on indefinite kernels. Frontiers of Computer Science, 13(4), 813-827, 2019.
  12. Yunyun Wang, Yan Meng, Yun Li, Songcan Chen, Zhenyong Fu, Hui Xue. Semi-superivsed manifold regularization with adaptive graph construction. Pattern Recognition Letters, 98(15), 90-95, 2017.[PDF]
  13. Yunyun Wang, Yan Meng, Zhengyong Fu, Hui Xue. Towards Safe Semi-supervised Classification: Adjusted Cluster Assumption via Clustering. Neural Processing Letters, 46(3): 1031-1042, 2017.[PDF]
  14. Qing Tian, Hui Xue, Lishan Qiao. Human age estimation by considering both the ordinality and similarity of ages. Neural Processing Letters, 43: 505-521, 2016.[PDF]
  15. 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, 38(11): 2335-2341, 2016.[PDF]
  16. Yunyun Wang, Songcan Chen, Hui Xue, Zhenyong Fu. Semi-supervised classification learning by discrimination-aware manifold regularization. Neurocomputing, 147: 299-306, 2015.[PDF]
  17. Jun Xie, Lu Yu, Lei Zhu, Hui Xue. Boosting decision stumps to do pairwise classification. Electronics Letters, 50(12): 866-867, 2014.[PDF]
  18. Hui Xue, Songcan Chen. Discriminality-driven regularization framework for indefinite kernel machine. Neurocomputing, 133: 209-221, 2014.[PDF]
  19. Hui Xue, Songcan Chen. Orthogonality-based label correction in multi-class classification. Electronics Letters, 49(12): 754-755, 2013.[PDF]
  20. Xiaohong Chen, Songcan Chen, Hui Xue. Universum linear discriminant analysis. Electronics Letters, 48(22): 1407-1408, 2012.[PDF]
  21. Yunyun Wang, Songcan Chen, Hui Xue. Can under-exploited structure of original-classes help ECOC-based multi-class classification?. Neurocomputing, 89: 158-167, 2012.[PDF]
  22. Xiaohong Chen, Songcan Chen, Hui Xue, Xudong Zhou. A unified dimensionality reduction framework for semi-paired and semi-supervised multi-view data. Pattern Recognition, 45(5): 2005-2018, 2012.[PDF]
  23. Xiaohong Chen, Songcan Chen, Hui Xue. Large correlation analysis. Applied Mathematics and Computation. 217(22): 9041-9052, 2011[PDF]
  24. 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]
  25. Hui Xue. Discriminative regularization: a new classifier learning method. Transactions of Nanjing University of Aeronautics & Astronautics, 26(1): 65-74, 2009.[PDF]
  26. Hui Xue, Songcan Chen, Qiang Yang. Structural regularized support vector machine: a framework for structural large margin classifier. IEEE Trans. on Neural Networks, 2011, 22(4): 573-587. [PDF]
  27. Hui Xue, Songcan Chen. Glocalization pursuit support vector machine. Neural Computing and Applications, 2011, 20(7): 1043-1053. [PDF]
  28. Yunyun Wang, Songcan Chen, Hui Xue. Support vector machines incorporated with feature discrimination. Expert Systems with Applications, 2011, 38: 12506-12513. [PDF]
  29. Yunyun Wang, Songcan Chen, Hui Xue. Structure-embedded AUC-SVM. International Journal of Pattern Recognition and Artificial Intelligence, 2010, 24(5): 667-690. [PDF]
  30. Zhe Wang, Songcan Chen, Hui Xue, Zhisong Pan. A novel regularization learning for single-view patterns: multi-view discriminative regularization. Neural Processing Letters, 2010, 31(3): 159-175. [PDF]
  31. Hui Xue, Songcan Chen, Qiang Yang. Discriminatively regularized least-squares classification. Pattern Recognition, 2009, 42(1): 93-104. .[PDF]
  32. Hui Xue, Yulian Zhu, Songcan Chen. Local ridge regression for face recognition. Neurocomputing, 2009, 72: 1342-1346. [PDF]
  33. Hui Xue, Songcan Chen, Xiaoqin Zeng. Classifier learning with a new locality regularization method. Pattern Recognition, 2008, 41(5): 1479-1490. [PDF]

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Courses

  1. Discrete Mathematics [打包下载]
  2. 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 Ch14 Ch15 Ch16








  3. Pattern Recognition [打包下载]
  4. 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








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Codes & Data

  1. The sourece code of Solving indefinite kernel support vector machine with difference of convex functions programming can be downloaded at [Matlab code]

 
 
 
 

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.