Chun-Guang Li

Research Direction: Machine Learning and Data Science
Tel: (+86 10) 62283059 Ext. 1007
Email: lichunguang AT bupt [dot] edu [dot] cn
Homepage in Chinese: Click Here
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About me:  I am currently an Associate Professor with the School of Information and Communication Engineering, at Beijing University of Posts and Telecommunications from Dec. 2007 and as a member of Pattern Recognition and Intelligent System (PRIS) lab. from Sept. 2002. I visited in the Vision, Dynamics and Learning lab at the Center for Imaging Science (CIS) in the Johns Hopkins University (JHU) from Dec. 2012 to Nov. 2013, and the Visual Computing group at Microsoft Research Asia from July 2011 to April 2012. I received Ph.D degree in signal and information processing from Beijing University of Posts and Telecommunications in Dec. 2007 and B.E. degree in telecommunication engineering from JiLin University in July 2002. My research interests focus on statistical learning especially for modeling with high dimensional data, including sparse/low-rank model, manifold/subspace clustering, matrix completion, semi-supervised learning and their applications in pattern recognition, computer vision, bioinformatics, and etc. I am a member of the IEEE, ACM, and CCF(China Computer Federation), and TC member of APSIPA(Asia-Pacific Signal and Information Processing Association).

Job & Professional Experience

Education

  • Sept 2002 – Dec. 2007 Ph.D in Signal and Information Processing, School of Information Engineering, Beijing University of Posts and Telecommunications, Beijing, P.R. China.
  • Sept. 1998 – July 2002 Bachelor in Telecommunication Engineering, School of Telecommunication Engineering, Jilin University, Changchun, Jilin, P.R. China.
Publications (* password will prompt when pointing the download link with your mouse)

I. Journal Articles

  • 2018
  • [11] Chun-Guang Li, Chong You, and René Vidal, “On Geometric Analysis of Affine Sparse Subspace Clustering“, IEEE Journal of Selected Topics in Signal Processing, Vol.12, Issue 6, pp.1-14, Dec. 2018. DOI: 10.1109/JSTSP.2018.2867446 [pdf]
    [10] Jianlou Si, Honggang Zhang, Chun-Guang Li, and Jun Guo, “Spatial Pyramid-Based Statistical Features for Person Re-Identification: A Comprehensive Evaluation”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol.48, No.7, pp.1140-1154, July 2018. DOI: 10.1109/TSMC.2016.2645660 [pdf][code]
    [9] Shuai Di, Honggang Zhang, Chun-Guang Li, Xue Mei, Danil Prokhorov, and Haibing Ling, “Cross-domain Traffic Scene Understanding: A Dense Correspondence based Transfer Learning Approach”, IEEE Transactions on Intelligent Transportation System, Vol.19, No. 3, pp.745-757, March, 2018. DOI: 10.1109/TITS.2017.2702012 [pdf]

  • 2017
  • [8] Chun-Guang Li, Chong You, and René Vidal, “Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework“, IEEE Transactions on Image Processing, Vol. 26, No. 6, pp.2988-3001, June 2017. DOI:10.1109/TIP.2017.2691557 [pdf][code]
    [7] Xianbiao Qi, Guoying Zhao, Chun-Guang Li, Jun Guo, Matti Pietikainen, “HEp-2 Cell Classification via Combining Multi-resolution Co-occurrence Texture and Large Regional Shape Information”, IEEE Journal of Biomedical and Health Informatics (J-BHI), Vol.21, No.2, pp.429-440, 2017. DOI: 10.1109/JBHI.2015.2508938 [pdf ][code]

  • 2016
  • [6] Chong You, Chun-Guang Li, Daniel Robinson, and Rene Vidal. “Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering”, Available on arXiv: 1605.02633, 2016. [pdf][code]
    [5] Chun-Guang Li and Rene Vidal. “A Structured Sparse plus Structured Low-Rank Framework for Subspace Clustering and Completion”, IEEE Transactions on Signal Processing, Vol. 64, No. 24, pp.6557-6570, Dec. 15, 2016. [pdf][code][data] DOI: 10.1109/TSP.2016.2613070
    [4] Xianbiao Qi, Chun-Guang Li, Guoying Zhao, Xiaopeng Hong, Matti Pietikainen, “Dynamic texture and scene classification by transferring deep image features”, Neurocomputing, Vol.171, 2016, pp:1230-1241.[pdf]

  • 2014
  • [3] Xianbiao Qi, Rong Xiao, Chun-Guang Li, Yu Qiao, Jun Guo, and Xiaoou Tang, “Pairwise Rotation Invariant Co-occurrence Local Binary Pattern“, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 36, No. 11, Nov. 2014, pp.2199-2213. DOI: 10.1109/TPAMI.2014.2316826 [pdf][code]

  • 2013
  • [2] Chun-Guang Li, Zhouchen Lin, and Jun Guo, “Bases Sorting: Generalizing the Concept of Frequency for Over-complete Dictionaries”, Neurocomputing, Vol.115, Sept. 4, 2013, pp.192–200. [pdf][code][data]

  • 2009
  • [1] Chun-Guang Li, Jun Guo, and Bo Xiao, “Intrinsic Dimensionality Estimation within Neighborhood Convex Hull“, International Journal of Pattern Recognition and Artificial Intelligence, Vol.23, No.1, Feb 2009, pp.31-44. [pdf]

    II. Conference Papers

  • 2018
  • [29] Chun-Guang Li, Junjian Zhang, and Jun Guo, “Constrained Sparse Subspace Clustering with Side Information”, accepted by International Conference on Pattern Recognition (ICPR), Aug. 20-24, Beijing, 2018.[pdf] (oral)
    [28] Ruopei Guo, Chun-Guang Li, Yonghua Li, and Jiaru Lin, “Density-Adaptive Kernel Ranking for Person Re-Identification”, accepted by International Conference on Pattern Recognition (ICPR), Aug. 20-24, Beijing, 2018.[pdf]
    [27] Jianlou Si, Honggang Zhang, Chun-Guang Li, Jason Kuen, Xiangfei Kong, Alex Kot, and Gang Wang, “Dual Attention Matching Networks for Context-Aware Feature Sequence based Person Re-Identification”, accepted by IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 19-21, 2018, Salt Lake City, USA.[pdf]

  • 2016
  • [26] Junjian Zhang, Chun-Guang Li, Honggang Zhang, and Jun Guo, “Low Rank and Structured Sparse Subspace Clustering”, In Proc. of IEEE International Conference on Visual Communication and Image Processing (VCIP), Nov. 27-30, 2016, Chengdu, China.[pdf]
    [25] Chong You, Chun-Guang Li, Daniel Robinson, and Rene Vidal. “Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering”, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 26-July 1, 2016, Lag Vegas, Nevada, US, pp.3928-3937. [pdf][code] (Oral, rate: <3.9%)

  • 2015
  • [24] Chun-Guang Li, Zhouchen Lin, Honggang Zhang, and Jun Guo, “Learning Semi-Supervised Representation Towards a Unified Optimization Framework for Semi-Supervised Learning“, In Proc. of IEEE International Conference on Computer Vision (ICCV), Dec. 11-18, 2015, pp.2767-2775, Santiago, Chile. [pdf][spotlight][poster][code] (An extended version with theoretical investigation and extensive experimental evaluations will be available soon)
    [23] Zhen Qin, Chun-Guang Li, Honggang Zhang, and Jun Guo, “Improving Tag Matrix Completion for Image Annotation and Retrieval”, In Proc. of IEEE International Conference on Visual Communication and Image Processing (VCIP), Dec. 13-16, 2015, Singapore.[pdf]
    [22] Chun-Guang Li, Chong You, and René Vidal, “On Sufficient Conditions for Affine Sparse Subspace Clustering“, In Signal Processing with Adaptive Sparse Structured Representations (SPARS) Workshop, July 6-9, 2015, Cambridge, UK.[pdf](An extended version will be available soon)
    [21] Jianlou Si, Honggang Zhang, and Chun-Guang Li, “Regularization in Metric Learning for Person Re-Identification“, In Proc. of IEEE Conference on Image Processing (ICIP), Sept. 27-30, 2015, Quebec, Canada.[pdf]
    [20] Chun-Guang Li and René Vidal, “Structured Sparse Subspace Clustering: A Unified Optimization Framework“, In Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.277-286, June 7-12, 2015, Boston, Massachusetts, US.[pdf][code]

  • 2014
  • [19] Jianlou Si, Honggang Zhang, and Chun-Guang Li, “Person Re-Identification via Region-of-Interest based Features“, In Proc. of IEEE Conference on Visual Communications and Image Processing (VCIP), Dec.7-10, 2014, Valletta, Malta.[pdf]

  • 2013
  • [18] Xianbiao Qi, Yu Qiao, Chun-Guang Li, and Jun Guo, “Exploring Cross-Channel Texture Correlation for Color Texture Classification“, British Machine Vision Conference (BMVC), Sept 9-13, 2013, Bristol, UK. [pdf]
    [17] Xianbiao Qi, Yu Qiao, Chun-Guang Li, and Jun Guo, “Multi-scale Joint Encoding of Local Binary Patterns for Texture and Material Classification“, British Machine Vision Conference (BMVC), Sept 9-13, 2013, Bristol, UK. [pdf]
    [16] Xianbiao Qi, Yi Lu, Shifeng Chen, Chun-Guang Li, and Jun Guo, “Spatial Co-Occurrence of Local Intensity Order for Face Recognition“, ICME Workshop on Management Information Systems (MIS) in Multimedia Art, Education, Entertainment, and Culture (MIS-MEDIA), July 15-19, 2013, San Jose, USA. [pdf]
    [15] Qiang Wang, Zhiyuan Guo, Gang Liu, Chun-Guang Li, Jun Guo, “Local alignment for query by humming“, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, May 2013.[pdf]

  • 2012
  • [14] Chun-Guang Li, Xianbiao Qi, and Jun Guo, “Dimensionality Reduction by Low-Rank Embedding“, The 2012 Sino-foreign-interchange Workshop on Intelligence Science and Intelligent Data Engineering (ISciDE2012), LNCS 7751, pp.181-188, 2013. [pdf]
    [13] Xianbiao Qi, Rong Xiao, Lei Zhang, Chun-Guang Li, and Jun Guo, “A Rapid Flower/Leaf Recognition System“, The 20th anniversary ACM Multimedia (ACM MM), 2012, Nara. [pdf]

  • 2011
  • [12] Chun-Guang Li, Xianbiao Qi, Jun Guo and Bo Xiao, “An Evaluation on Different Graphs for Semi-supervised Learning”, The 2011 Sino-foreign-interchange Workshop on Intelligence Science and Intelligent Data Engineering (ISciDE2011), LNCS 7202, pp. 58-65, Feb. 2012. [pdf]

  • 2010
  • [11] Chun-Guang Li, Jun Guo and Hong-gang Zhang, “Local Sparse Representation based Classification”, The 20th International Conference on Pattern Recognition (ICPR), August 23-26, 2010, Istanbul, Turkey. [pdf]

  • 2009
  • [10] Qianfang Xu, Chun-Guang Li, Bo Xiao, Jun Guo, “A Visualization Algorithm for Alarm Association Mining”, International Conference on Network Infrastructure and Digital Content, pp. 326-330, 2009.[pdf]
    [9] Chun-Guang Li, Jun Guo, and Hong-gang Zhang, “Learning Bundle Manifold by Double Neighborhood Graphs“, The 9th Asian Conference on Computer Vision (ACCV), 2009, LNCS 5996, Part III, pp. 321-330. [pdf][code]
    [8] Chuang Zhang, Ming Wu, Chun-Guang Li, Bo Xiao, Zhiqing Lin, “Resume Parser: Semi-structured Chinese Document Analysis“, CSIE (5), 2009, pp.12-16. [pdf]
    [7] Hong-gang Zhang, Jun Guo, Guang Chen, and Chun-Guang Li, “HCL2000 — A Large-scale Handwritten Chinese Character Database for Handwritten Character Recognition“, ICDAR 2009, pp.286-290. [pdf][data ][code:HCL2000 I/O]

  • 2007
  • [6] Chun-Guang Li, Jun Guo, and Xiangfei Nie, “Intrinsic Dimensionality Estimation with Neighborhood Convex Hull”, Proceeding of the International Conference on Computational Intelligence and Security, 2007. [pdf]
    [5] Chun-Guang Li, Jun Guo, and Hong-gang Zhang, “Pruning Neighborhood Graph for Geodesic Distance based Semi-Supervised Classification“, Proceeding of the International Conference on Computational Intelligence and Security 2007, pp.428-432. [pdf]

  • 2006
  • [4] Xiangfei Nie, Jun Guo, Zhen Yang, Chun-Guang Li, Jian Wang, Weihong Deng, “EMD Based Face Gender Discrimination“, The Sixth World Congress on Intelligent Control and Automation (WCICA), Vol.1, pp. 4078-4081, 2006.[pdf]
    [3] Chun-Guang Li, Jun Guo, and Xiangfei Nie, “Learning geodesic metric for out-of-sample extension of isometric embedding“, Proceeding of the International Conference on Computational Intelligence and Security 2006, Part I, 2006, pp.449-452. [pdf]
    [2] Chun-Guang Li and Jun Guo, “Supervised Isomap with explicit mapping“, Proceeding of the First International Conference on Innovative Computing, Information and Control, Vol.3, 2006, pp.345-348. [pdf][code]
    [1] Chun-Guang Li, Jun Guo, Guang Chen, Xiangfei Nie, and Zhen Yang, “A version of Isomap with explicit mapping“, Proceeding of the International Conference on Machine Learning and Cybernetics, Vol.6, 2006, pp.3201-3206. [pdf]

    III. Journal Papers (In Chinese)

  • 2008
  • [3] Bo Xiao, Qian-Fang Xu, Zhiqing Lin, Jun Guo and Chun-Guang Li, “Credible Association Rule and Its Mining Algorithm Based on Maximum Clique”, Journal of Software, Vol.19,No.10,2008,pp.2597-2610.[In Chinese][pdf]

  • 2007
  • [2] Xiang-Fei Nie, Chun-Guang Li and Jun Guo, “Face recognition based on Gabor wavelet and locally linear embedding”, Computer Engineering and Applications, Vol.43, No. 18, 2007, pp.62-64.[In Chinese]
    [1] Xiang-Fei Nie, Chun-Guang Li and Jun Guo, “Face Detection Based on Empirical Mode Decomposition and Matching Pursuit”, Computer Engineering, Vol.33, No.14, July, 2007, pp.30-33.[In Chinese]

    IV. PhD Thesis: “Manifold Learning and its Applications in Pattern Recognition”, Beijing University of Posts and Telecommunications, Dec. 2007. [pdf]

    Languages:

    • [1] Chinese
    • [2] Japanese
    • [3] English

    Teaching Activities:

    1. Discrete Mathematics [2008 Spring]
    2. Digital Signal Processing [2009 Fall]
    3. Basics in Bioinformatics [2012 Spring][2014-2015 Fall][2016 Fall][2017 Fall]:
      In this course we will introduce how to use computer to handle bioinformatics data. The contents cover the following topics: (1) Brief history of bioinformatics; (2) Basics in model biology; (3) Frequently used bioinformatics database; (4) Sequence analysis: theory, algorithms, and applications; (5) Protein structures and functions prediction; (6) Gene expression data analysis and etc.
    4. Neural Computation: [2008-2012 Spring] [2014-2016 Spring]:This course covers majority of machine learning techniques. Topics Can be divided into three parts: (1) The classical topics in neural networks, e.g., Perceptron, Multilayer Perceptron(MLP), Regularized Networks, and Self-Organization Map (SOM), and Deep Networks; (2) A series of statistical learning theories, e.g., the classical error analysis via bias-variance decomposition, statistical learning theory (Vapanik’s) and VC-dimension, regularization theory, and etc.; (3) The related learning machines (algorithms), as applications of the aforementioned learning theory, e.g. bagging, boosting (AdaBoost), Mixture of Experts, Decision Tree, Support Vector Machine, Kernel Methods and Kernel Machine, Regularization networks, and other active topics in recent machine learning community, e.g., Manifold Learning, Subspace Clustering, Compressed Sensing, Sparse Representation, Dictionary Learning, Low-Rank Representation, Matrix Completion and Sensing.
    5. Pattern Recognition [2014 Fall]
    6. Machine Learning and Data Science  [2017 Spring][2018 Spring]

    Academic Service and Activity:

    • As a reviewer for SPARS, Natl. Science Review, IEEE TPAMI / TSP / TIP / TNNLS / TBME / TCYB / TCSVT, PR, Neurocom, DMKD, AI Review, SP:Image Comm., Soft Computing, PRL, NCAA, IJPRAI, AAAI, ACM MM, ICPR, and etc.
    • As a member of TPC of ACM MM / CCF-CV / CSIG-MV.
    • As a member of IEEE / ACM / CCF / CSIG.

    Invited Talks:

    Other Links:

    1.  Writing & Revision [link][link]
    2.  Ten Simple Rules for Mathematical Writing – [link]
    3.  Mathematics – Stack Exchange – [link]
    4.  Academic Lecture Videos – [link]
    5.  List of some journal impact factors – [link]
    6.  Comments on SCI-Journals – [link]
    7.  List of Computer Science Conference – [link]
    8.  Microsoft Academic Search – [link]
    9.  The Psychology of Luck – [link]
    10.  Dodo’s Pattern Recognition Commune – [link]
    11.  Preprint Papers – [link]
    12.  Compressed Sensing Resource – [link] [link]
    13.  Resource on Sensing and Analysis of High-dimensional Data – [link] [link]
    14.  Machine Learning (Theory) – [link]
    15.  Research Links: Machine Learning/Compressed Sensing /Action /Activity /Feature /Optimization/Subspace – [link]
    16.  Manifold Learning Resource – [ISOMAP][LLE][LaplacianEigenmap][ManifoldCharting][HessianLLE][LTSA][SDE][Logmap][DiffusionMaps][spectralmethod][comparison][survey]
    17. Modeling with High Dimensional Data: [subspace clustering] [Scalable Sparse Subspace Clustering] [Sparse and Low-Rank Model for Visual Analytics] [link]