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Chris H Q Ding

Name

[Ding, Chris H Q]
  • Professor

Professional Preparation

    • 1987 Ph.D. in PhysicsColumbia University
    • 1985 M.Ph. in PhysicsColumbia University
    • 1983 M.A. in PhysicsColumbia University

Appointments

    • Jan 2007 to Present Professor
      University of Texas at Arlington

Publications

      Conference Proceeding 2010 2010
      • Hua Wang, Chris H. Q. Ding, Heng Huang: Multi-Label Classification: Inconsistency and Class Balanced K-Nearest Neighbor. AAAI 2010
        {Conference Proceeding }
      2010 2010
      • Qi Liu, Enhong Chen, Hui Xiong, Chris H. Q. Ding: Exploiting user interests for collaborative filtering: interests expansion via personalized ranking. CIKM 2010: 1697-1700
        {Conference Proceeding }
      2010 2010 2010 2010 2010
      • Quanquan Gu, Jie Zhou, Chris H. Q. Ding: Collaborative Filtering: Weighted Nonnegative Matrix Factorization Incorporating User and Item Graphs. SDM 2010: 199-210
        {Conference Proceeding }
      2010 2010
      • Dingding Wang, Tao Li, Chris H. Q. Ding: Weighted Feature Subset Non-negative Matrix Factorization and Its Applications to Document Understanding. ICDM 2010: 541-550
        {Conference Proceeding }
      2010
      • Dijun Luo, Chris H. Q. Ding, Heng Huang: Towards Structural Sparsity: An Explicit l2/l0 Approach. ICDM 2010: 344-353
        {Conference Proceeding }
      2010
      • Li Zheng, Tao Li, Chris H. Q. Ding: Hierarchical Ensemble Clustering. ICDM 2010: 1199-1204
        {Conference Proceeding }

      Journal Article 2010
      • Luo, H. H.; Ding, F. N. On the Eigenvectors of p-Laplacian. Machine Learning 2010, 81 (1), 37-51.
        {Journal Article }
      2010
      • Zhang, T. L.; Chris, H. Q.; Ding, X. W. R.; Zhang, X. Binary matrix factorization for analyzing gene expression data. Data Mining and Knowledge Discovery 2010, 20 (1), 28-52.
        {Journal Article }
      2010
      • H. Q. Chris, T. L. Ding, and M. I. Jordan. "Convex and Semi-Nonnegative Matrix Factorizations," IEEE Trans. Pattern Analysis & Machine Intelligence, vol. 32, no. 1, pp. 45-55, 2010.
        {Journal Article }

      Conference Proceeding 2008
      • Heng Huang, Chris H. Q. Ding: Robust tensor factorization using R1 norm. CVPR 2008
        {Conference Proceeding }
      2008
      • Chris H. Q. Ding, Heng Huang, Dijun Luo: Tensor reduction error analysis - Applications to video compression and classification. CVPR 2008
        {Conference Proceeding }
      2008 2008
      • Heng Huang, Chris H. Q. Ding, Dijun Luo, Tao Li: Simultaneous tensor subspace selection and clustering: the equivalence of high order svd and k-means clustering. KDD 2008: 327-335
        {Conference Proceeding }
      2008 2008
      • Tao Li, Chris H. Q. Ding: Weighted Consensus Clustering. SDM 2008: 798-809
        {Conference Proceeding }
      2008 2008
      • Chris H. Q. Ding, Tao Li, Michael I. Jordan: Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding. ICDM 2008: 183-192
        {Conference Proceeding }

      Journal Article 2008 2008
      • Chris, H. Q.; Ding, T. L.; Peng, W. On the equivalence between Non-negative Matrix Factorization and Probabilistic Latent Semantic Indexing. Computational Statistics & Data Analysis 2008, 52 (8), 3913-3927.
        {Journal Article }
      2008
      • Tseng, C. H. Q. Efficient Parallel I/O in Community Atmosphere Model (CAM). International Journal of High Performance Computing Applications 2008, 22 (2), 206-218.
        {Journal Article }

      Conference Proceeding 2007
      • Chris H. Q. Ding, Tao Li: Adaptive dimension reduction using discriminant analysis and K-means clustering. ICML 2007: 521-528
        {Conference Proceeding }
      2007
      • Yi Zhang, Chris H. Q. Ding, Tao Li: A Two-Stage Gene Selection Algorithm by Combining ReliefF and mRMR. BIBE 2007: 164-171
        {Conference Proceeding }
      2007 2007
      • Chris H. Q. Ding, Rong Jin, Tao Li, Horst D. Simon: A learning framework using Green's function and kernel regularization with application to recommender system. KDD 2007: 260-269
        {Conference Proceeding }
      2007 2007
      • Tao Li, Chris H. Q. Ding, Michael I. Jordan: Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization. ICDM 2007: 577-582
        {Conference Proceeding }

      Conference Proceeding 2006 2006
      Journal Article 2006
      • M. Andy, C. H. Q. Yip, and T. F. C. Ding. "Dynamic Cluster Formation Using Level Set Methods," IEEE Trans. Pattern Analysis & Machine Intelligence, vol. 28, no. 6, pp. 877-889, 2006.
        {Journal Article }

      Journal Article 2005
      • F. L. Peng and C. H. Q. Ding. "Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy.," IEEE Trans. Pattern Analysis & Machine Intelligence, vol. 27, no. 8, pp. 1226-1238, 2005.
        {Journal Article }

      Journal Article 2004
      • Ding, H. Z.; He, P. H.; Simon, H. D. Link Analysis: Hubs and Authorities on the World Wide Web. SIAM Review 2004, 46 (1), 256-268.
        {Journal Article }

Support & Funding

This data is entered manually by the author of the profile and may duplicate data in the Sponsored Projects section.
    • Jan 2009 to Jan 2012 Non-negative Matrix Factorizations for Data Mining: Foundations, Capabilities, and Applications sponsored by  - $200000
    • Jan 2009 to Jan 2012 New Theoretical Foundations of Tensor Applications: Clustering, Error Analysis, Global Convergence, and Robust Formulations sponsored by  - $250833
    • Jan 2008 to Jan 2011 Matrix-Model Machine Learning: Unifying Machine Learning and Scientific Computing sponsored by  - $115983

Courses

      • CSE 5311-004 DATA MINING

        Data mining (DM) is often refered as knowledge discovery in database (KDD).
        Today, DM is a broad area of data analysis, exploration, using
        techniques from Machine Learning, Artificial Intelligence, Statistics and Database.
        This course will cover main topics, including
        classification, clustering, association rule discovery, feature selection, dimension reduction.
         

        Spring - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • CSE 5334-001 DATA MINING

        Data mining (DM) is often refered as knowledge discovery in database (KDD).
        Today, DM is a broad area of data analysis, exploration, using
        techniques from Machine Learning, Artificial Intelligence, Statistics and Database.
        This course will cover main topics, including
        classification, clustering, association rule discovery, feature selection, dimension reduction.
         

        Spring - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • CSE 5311-004 DESIGN AND ANALYSIS OF ALGORITHMS

        Computer algorithms is at the heart of computer sciences. Algorithms are used everywhere, from operating systems to databases, to solving a variety of optimization problems. This course will cover all major areas of algorithms: sorting algorithms, greedy algorithms, graph algorithms, dynamical programming, maximum flow problems, string matching algorithms, geometric algorithms, and randomized algorithms.

        Besides above traditional algorithms, several state-of-art practical algorithms will be covered: web ranking algorithms, social network algorithms, data mining algorithms, computational biology algorithms.

        Major ideas are introduced through examples and historical perspectives, so that students will have a grasp on the evolution and development of algorithms.

        Will cover algorithm analysis on runtime and memory usage, recurrence relations, advanced data structures, NP-completeness.

        Class projects are required to practice the algorithms learned in the class.

        After completing this course, students will have the ability to independently investigate a computational problem, design a practical algorithm to solve it and analyze the performance of the algorithm.  

        Spring - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours1 Link
      • CSE 6339-001 Web Search, Mining, and Integration
        No Description Provided.
        Spring - Regular Academic Session - 2012