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WU, Xiao-Ming

Assistant Professor, Computing@PolyU Hong Kong

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About Me

I am currently an assistant professor in the Department of Computing, The Hong Kong Polytechnic University. I obtained my PhD degree from the Department of Electrical Engineering, Columbia University, with my thesis titled as "Learing on Graphs with Partially Absorbing Random Walks: Theory and Practice". Prior to that, I studied in the Department of Information Engineering, The Chinese University Of Hong Kong, where I obtained a MPhil degree. Before coming to Hong Kong, I studied in Peking University, where I received my BSc degree from the School of Mathematical Sciences, and my MSc degree from the Instituite of Computer Science and Technology.

Research

My research interests are in machine learning, artificial intelligence, and data mining. I was drawn to the discipline of machine learning by the way it blends mathematics and real applications. I am mostly interested in developing methods for analyzing data with graph structure, which have numerous applications in areas such as social network analysis, information retrieval, knowledge discovery, natural language processing, computer vision, and bioinformatics. On the theory side, I work on the development of understanding of the principles of practical methods. For example, under what circumstance one method is better than another, and when a particular assumption breaks down. I usually end up gaining new insights by studying such questions, and then apply them to design novel and robust methods which are also computationally tractable. Some topics I have worked on include

Selected Publications

  • New Insights into Laplacain Similarity Search.
    Xiao-Ming Wu, Zhenguo Li, and Shih-Fu Chang.
    In Proceedings of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2015
    [PDF] [Supplemental] [Abstract] [Code] [Poster]
  • Locally Linear Hashing for Extracting Non-Linear Manifolds.
    Go Irie, Zhenguo Li, Xiao-Ming Wu, and Shih-Fu Chang.
    In Proceedings of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2014.
    [PDF] [Supplemental] [Code] [Poster]
  • Analyzing the Harmonic Structure in Graph-Based Learning.
    Xiao-Ming Wu, Zhenguo Li, and Shih-Fu Chang.
    In Proceedings of Advances in Neural Information Processing Systems (NIPS), December 2013.
    [PDF] [Supplemental] [Code] [Poster]
  • Learning with Partially Absorbing Random Walks.
    Xiao-Ming Wu, Zhenguo Li, Anthony Man-Cho So, John Wright, and Shih-Fu Chang.
    In Proceedings of Advances in Neural Information Processing Systems (NIPS), December 2012.
    [PDF] [Supplemental] [Code] [Poster]
  • Segmentation Using Superpixels: A Bipartite Graph Partitioning Approach.
    Zhenguo Li, Xiao-Ming Wu, and Shih-Fu Chang.
    In Proceedings of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2012.
    [PDF] [Code] [Project][Poster]
  • Fast Graph Laplacian Regularized Kernel Learning via Semidefinite-Quadratic-Linear Programming.
    Xiao-Ming Wu, Anthony Man-Cho So, Zhenguo Li, and Shuo-Yen Robert Li.
    In Proceedings of Advances in Neural Information Processing Systems (NIPS), December 2009 (Spotlight).
    [PDF] [Code] [Poster]

My Group

I am lucky to work with brilliant students who are willing to follow my research interests, and tackle research problems with me. Our current team members include

Teaching Subjects

I have enjoyed teaching the following subjects.

Contact

The best way to reach me is by email. Due to the large volume of emails recieved, I could not respond to every enquiry, but I do read every email.