Home Projects Publications Teaching Supervision Services Vacancies
  1. Jinfeng Li, Xiao Yan, Jian Zhang, An Xu, James Cheng, Jie Liu, Kelvin Ng, and Ti-Chung Cheng.
    A General and Efficient Querying Method for Learning to Hash.
    In Proceedings of the 37th ACM SIGMOD International Conference on Management of Data, Pages ???-???, 2018. (SIGMOD 2018)

  2. Yuanyuan Liu, Fanhua Shang, James Cheng, Hong Cheng, and Licheng Jiao.
    Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds.
    In Proceedings of the 30th Annual Conference on Neural Information Processing Systems, Pages ???-???, 2017. (NIPS 2017)

  3. Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, and Zhouchen Lin.
    Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Volume ??, Number ??, Pages ???-???, 2017.

  4. Da Yan, Yuzhen Huang, Miao Liu, Hongzhi Chen, James Cheng, Huanhuan Wu, and Chengcui Zhang.
    GraphD: Distributed Vertex-Centric Graph Processing Beyond the Memory Limit.
    IEEE Transactions on Parallel and Distributed Systems (TPDS), Volume ??, Number ??, Pages ???-???, 2017. [code]

  5. Jinfeng Li, James Cheng, Fan Yang, Yuzhen Huang, Yunjian Zhao, Xiao Yan, and Ruihao Zhao.
    LoSHa: A General Framework for Scalable Locality Sensitive Hashing.
    In Proceedings of the 40th International ACM SIGIR conference on Research and Development in Information Retrieval, Pages ???-???, 2017. (SIGIR 2017)

  6. Qizhen Zhang, Hongzhi Chen, Da Yan, James Cheng, Boon Thau Loo, and Purushotham Bangalore.
    Architectural Implications on the Performance and Cost of Graph Analytics Systems.
    In Proceedings of the 2017 ACM Symposium on Cloud Computing, Pages ???-???, 2017. (SoCC 2017)

  7. Fanhua Shang, Yuanyuan Liu, James Cheng, and Da Yan.
    Fuzzy Double Trace Norm Minimization for Recommendation Systems.
    IEEE Transactions on Fuzzy Systems (TFS), Volume ??, Number ??, Pages ???-???, 2017.

  8. Fan Yang, Fanhua Shang, Yuzhen Huang, James Cheng, Jinfeng Li, Yunjian Zhao, and Ruihao Zhao.
    LFTF: A Framework for Efficient Tensor Analytics at Scale.
    PVLDB, Volume 10, Number 7, Pages ???-???, 2017. (VLDB 2017)

  9. Yuanyuan Liu, Fanhua Shang, and James Cheng.
    Accelerated Variance Reduced Stochastic ADMM.
    In Proceedings of the 31st AAAI Conference on Artificial Intelligence, Pages ???-???, 2017. (AAAI 2017)

  10. Fan Yang, Yuzhen Huang, Yunjian Zhao, Jinfeng Li, Guanxian Jiang, and James Cheng.
    The Best of Both Worlds: Big Data Programming with Both Productivity and Performance.
    In Proceedings of the 36th ACM SIGMOD International Conference on Management of Data, Pages ???-???, 2017. (SIGMOD 2017)

  11. Zhiqiang Xu, James Cheng, Xiaokui Xiao, Ryohei Fujimaki, and Yusuke Muraoka.
    Efficient Nonparametric and Asymptotic Bayesian Model Selection Methods for Attributed Graph Clustering.
    Knowledge and Information Systems Journal (KAIS), Volume ?, Number ?, Pages ???-???, 2017.

  12. Huanhuan Wu, Yunjian Zhao, James Cheng, and Da Yan.
    Efficient Processing of Growing Temporal Graphs.
    In Proceedings of the 22nd International Conference on Database Systems for Advanced Applications, Pages ???-???, 2017. (DASFAA 2017)

  13. Jinfeng Li, James Cheng, Yunjian Zhao, Fan Yang, Yuzhen Huang, Haipeng Chen, and Ruihao Zhao.
    A Comparison of General-Purpose Distributed Systems for Data Processing.
    In Proceedings of the 2016 IEEE International Conference on Big Data, Pages ???-???, 2016. (IEEE BigData 2016)

  14. Yi Yang, Da Yan, Huanhuan Wu, James Cheng, Shuigeng Zhou, and John C.S. Lui.
    Diversified Temporal Subgraph Pattern Mining.
    In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Pages ???-???, 2016. (KDD 2016) [code]

  15. Da Yan, James Cheng, M. Tamer Ozsu, Fan Yang, Yi Lu, John C.S. Lui, Qizhen Zhang, and Wilfred Ng.
    A General-Purpose Query-Centric Framework for Querying Big Graphs [Innovative Systems Track].
    PVLDB, Volume 9, Number 7, Pages 564-575, 2016. (VLDB 2016) [code]

  16. Fan Yang, Jinfeng Li, and James Cheng.
    Husky: Towards a More Efficient and Expressive Distributed Computing Framework.
    PVLDB, Volume 9, Number 5, Pages 420-431, 2015. (VLDB 2016) [link to the husky project]

  17. Huanhuan Wu, James Cheng, Yiping Ke, Silu Huang, Yuzhen Huang, and Hejun Wu.
    Efficient Algorithms for Temporal Path Computation.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume ?, Number ?, Pages ??-??, 2016. [code]

  18. Huanhuan Wu, Yuzhen Huang, and James Cheng, Jinfeng Li, and Yiping Ke.
    Reachability and Time-Based Path Queries in Temporal Graphs.
    In Proceedings of the 32nd IEEE International Conference on Data Engineering, Pages ???-???, 2016. (ICDE 2016) [code]

  19. Fanhua Shang, Yuanyuan Liu, and James Cheng.
    Unified Scalable Equivalent Formulations for Schatten Quasi-Norms.
    CUHK Technical Report CSE-ShangLC20160307, 2016.

  20. Fanhua Shang, Yuanyuan Liu, and James Cheng.
    Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization.
    In Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, Pages ???-???, 2016. (AISTATS 2016, full oral presentation)

  21. Fanhua Shang, Yuanyuan Liu, and James Cheng.
    Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization.
    In Proceedings of the 30th AAAI Conference on Artificial Intelligence, Pages ???-???, 2016. (AAAI 2016, full oral presentation)

  22. Qizhen Zhang, Da Yan, and James Cheng.
    Quegel: A General-Purpose System for Querying Big Graphs.
    In Proceedings of the 35th ACM SIGMOD International Conference on Management of Data, Pages ???-???, 2016. (SIGMOD 2016)

  23. Da Yan, Yingyi Bu, Yuanyuan Tian, Amol Deshpande, and James Cheng.
    Big Graph Analytics Systems.
    In Proceedings of the 35th ACM SIGMOD International Conference on Management of Data, Pages ???-???, 2016.

  24. Cheng Chen, Hejun Wu, Da Yan, and James Cheng.
    SGraph: A Distributed Streaming System For Processing Big Graphs.
    In Proceedings of the 2nd International Conference on Big Data Computing and Communication, Pages ???-???, 2016. (BIGCOM 2016)

  25. Yanyan Xu, James Cheng, and Ada Fu.
    Distributed Maximal Clique Computation and Management.
    IEEE Transactions on Services Computing, Volume ??, Number ??, Pages ???-???, 2015.

  26. Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, and Hong Cheng.
    Generalized Higher-Order Orthogonal Iteration for Tensor Learning and Decomposition.
    IEEE Transactions on Neural Networks and Learning Systems, Volume ??, Number ??, Pages ???-???, 2015.

  27. Huanhuan Wu, James Cheng, Yi Lu, Yiping Ke, Yuzhen Huang, Da Yan, and Hejun Wu.
    Core Decomposition in Large Temporal Graphs.
    In Proceedings of the 2015 IEEE International Conference on Big Data, Pages 649-658, 2015. (IEEE BigData 2015) [code]

  28. Da Yan, James Cheng, Yi Lu, and Wilfred Ng.
    Effective Techniques for Message Reduction and Load Balancing in Distributed Graph Computation.
    In Proceedings of the 24th International World Wide Web Conference, Pages 1307-1317, 2015. (WWW 2015) [code]

  29. Yi Lu, James Cheng, Da Yan, and Huanhuan Wu.
    Large-Scale Distributed Graph Computing Systems: An Experimental Evaluation.
    PVLDB, Volume 8, Number 3, Pages 281-292, 2014. (VLDB 2015) [code]

  30. Da Yan, James Cheng, Yi Lu, and Wilfred Ng.
    Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs.
    PVLDB, Volume 7, Number 14, Pages 1981-1992, 2014. (VLDB 2014) [code]

  31. Da Yan, James Cheng, Kai Xing, Yi Lu, Wilfred Ng, and Yingyi Bu.
    Pregel Algorithms for Graph Connectivity Problems with Performance Guarantees.
    PVLDB, Volume 7, Number 14, Pages 1821-1832, 2014. (VLDB 2014) [code]

  32. Yuanyuan Liu, Fanhua Shang, Licheng Jiao, James Cheng, and Hong Cheng.
    Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data.
    IEEE Transactions on Cybernetics, Volume 45, Number 11, Pages 2437-2448, 2015.

  33. Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, and Hong Cheng.
    Robust Bilinear Factorization with Missing and Grossly Corrupted Observations.
    Information Sciences, Volume 307, Pages 53-72, 2015.

  34. Fanhua Shang, Yuanyuan Liu, James Cheng, and Hong Cheng.
    Recovering Low-Rank and Sparse Matrices via Robust Bilateral Factorization.
    In Proceedings of the 14th IEEE International Conference on Data Mining, Pages ???-???, 2014. (ICDM 2014)

  35. Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, and Hong Cheng.
    Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion.
    In Proceedings of the 27th Annual Conference on Neural Information Processing Systems, Pages 1763-1771, 2014. (NIPS 2014)

  36. Da Yan, James Cheng, Zhou Zhao, and Wilfred Ng.
    Efficient Location-based Search of Trajectories with Location Importance.
    Knowledge and Information Systems Journal (KAIS), Volume ?, Number ?, Pages ???-???, 2014.

  37. Zhou Zhao, James Cheng, Wilfred Ng, Furu Wei, Ming Zhou, and Yingjun Wu.
    SocialTransfer: Transferring Social Knowledge for Cold-Start Crowdsourcing.
    In Proceedings of the 23rd ACM International Conference on Information and Knowledge Management, Pages ???-???, 2014. (CIKM 2014)

  38. Zhou Zhao, James Cheng, and Wilfred Ng.
    Truth Discovery in Data Streams: A Single-Pass Probabilistic Approach.
    In Proceedings of the 23rd ACM International Conference on Information and Knowledge Management, Pages ???-???, 2014. (CIKM 2014)

  39. Fanhua Shang, Yuanyuan Liu, James Cheng, and Hong Cheng.
    Robust Principal Component Analysis with Missing Data.
    In Proceedings of the 23rd ACM International Conference on Information and Knowledge Management, Pages ???-???, 2014. (CIKM 2014)

  40. Yanyan Xu, James Cheng, Ada Fu, and Yingyi Bu.
    Distributed Maximal Clique Computation.
    In Proceedings of the 3rd IEEE International Congress on Big Data, Pages ???-???, 2014. (IEEE BigData 2014) [code]
    [The Best Student Paper Award]

  41. Jia Wang, Ada Fu, and James Cheng.
    Rectangle Counting in Large Bipartite Graphs.
    In Proceedings of the 3rd IEEE International Congress on Big Data, Pages ???-???, 2014. (IEEE BigData 2014)

  42. James Cheng, Zechao Shang, Hong Cheng, Haixun Wang, and Jeffrey Xu Yu.
    Efficient Processing of K-Hop Reachability Queries.
    International Journal on Very Large Data Bases (VLDBJ), Volume 23, Number 2, Pages 227-252, 2014.
    [Special issue on best papers of VLDB 2012] [code]

  43. Zhiqiang Xu, Yiping Ke, YiWang, Hong Cheng, and James Cheng.
    GBAGC: A General Bayesian Framework for Attributed Graph Clustering.
    ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 9, Number 1, Pages 5:1-43, 2014. [code]

  44. Fanhua Shang, Yuanyuan Liu, and James Cheng.
    Generalized Higher-Order Tensor Decomposition via Parallel ADMM.
    In Proceedings of the 28th AAAI Conference on Artificial Intelligence, Pages 1279-1285, 2014. (AAAI 2014)

  45. Yuanyuan Liu, Fanhua Shang, Hong Cheng, and James Cheng.
    Nuclear Norm Regularized Least Squares Optimization on Grassmannian Manifolds.
    In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, Pages 515-524, 2014. (UAI 2014)

  46. Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng, and Hanghang Tong.
    Factor Matrix Trace Norm Minimization for Low-Rank Tensor Completion.
    In Proceedings of the 14th SIAM International Conference on Data Mining, Pages 866-874, 2014. (SDM 2014)

  47. Linhong Zhu, Aram Galstyan, James Cheng, and Kristina Lerman.
    Tripartite Graph Clustering for Dynamic Sentiment Analysis on Social Media.
    In Proceedings of the 33rd ACM SIGMOD International Conference on Management of Data, Pages 1531-1542, 2014. (SIGMOD 2014) [code]

  48. Huanhuan Wu, James Cheng, Silu Huang, Yiping Ke, Yi Lu, and Yanyan Xu.
    Path Problems in Temporal Graphs.
    PVLDB, Volume 7, Number 9, Pages 721-732, 2014. (VLDB 2014) [code]

  49. Jia Wang, James Cheng, and Ada Fu.
    Redundancy-Aware Maximal Cliques.
    In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Pages 122-130, 2013. (SIGKDD 2013) [code]

  50. James Cheng, Silu Huang, Huanhuan Wu, and Ada Fu.
    TF-Label: a Topological-Folding Labeling Scheme for Reachability Querying in a Large Graph.
    In Proceedings of the 32nd ACM SIGMOD International Conference on Management of Data, Pages 193-204, 2013. (SIGMOD 2013) [code]

  51. Da Yan, James Cheng, Wilfred Ng, and Kin Sum Liu.
    Finding Distance-Preserving Subgraphs in Large Road Networks.
    In Proceedings of the 29th IEEE International Conference on Data Engineering, Pages 625-636, 2013. (ICDE 2013) [code]

  52. Ada Fu, Huanhuan Wu, James Cheng, and Raymond Wong.
    IS-LABEL: an Independent-Set based Labeling Scheme for Point-to-Point Distance Querying.
    PVLDB, Volume 6, Number 6, Pages 457-468, 2013. (VLDB 2013) [code]

  53. Wenting Liu, Guangxia Li, and James Cheng.
    Fast PageRank Approximation by Adaptive Sampling.
    Knowledge and Information Systems Journal (KAIS), Volume 42, Number 1, Pages 127-146, 2013.

  54. James Cheng, Linhong Zhu, Yiping Ke, and Shumo Chu.
    Fast Algorithms for Maximal Clique Enumeration with Limited Memory.
    In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Pages 1240-1248, 2012. (SIGKDD 2012)

  55. James Cheng, Yiping Ke, Shumo Chu, and Carter Cheng.
    Efficient Processing of Distance Queries in Large Graphs: A Vertex Cover Approach.
    In Proceedings of the 31st ACM SIGMOD International Conference on Management of Data, Pages 457-468, 2012. (SIGMOD 2012)

  56. Zhiqiang Xu, Yiping Ke, Yi Wang, Hong Cheng, and James Cheng.
    A Model-based Approach to Attributed Graph Clustering.
    In Proceedings of the 31st ACM SIGMOD International Conference on Management of Data, Pages 505-516, 2012. (SIGMOD 2012) [code]

  57. Shumo Chu and James Cheng.
    Triangle Listing in Massive Networks.
    ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 6, Number 4, Pages 17:1-32, 2012.
    [Special issue on best papers of SIGKDD 2011]

  58. James Cheng, Zechao Shang, Hong Cheng, Haixun Wang, and Jeffrey Xu Yu.
    KReach: Who is In Your Small World.
    PVLDB, Volume 5, Number 11, Pages 1292-1303, 2012. (VLDB 2012) [code]

  59. Jia Wang and James Cheng.
    Truss Decomposition in Massive Networks.
    PVLDB, Volume 5, Number 9, Pages 812-823, 2012. (VLDB 2012)

  60. Wenqing Lin, Xiaokui Xiao, James Cheng, and Sourav Bhowmick.
    Efficient Algorithms for Generalized Subgraph Query Processing.
    In Proceedings of the 21st ACM International Conference on Information and Knowledge Management, Pages 325-334, 2012. (CIKM 2012) [code]

  61. James Cheng, Yiping Ke, Ada Fu, Jeffrey Yu, and Linhong Zhu.
    Finding Maximal Cliques in Massive Networks.
    ACM Transactions on Database Systems (TODS), Volume 36, Number 4, Pages 21:1-34, 2011.
    [Special issue on best papers of SIGMOD 2010] [code]

  62. James Cheng, Yiping Ke, Ada Fu, and Jeffrey Yu.
    Fast Graph Query Processing with a Low-Cost Index.
    International Journal on Very Large Data Bases (VLDBJ), Volume 20, Number 4, Pages 521-539, 2011. [code]

  63. Linhong Zhu, Wee Keong Ng, and James Cheng.
    Structure and Attribute Index for Approximate Graph Matching in Large Graphs.
    Information Systems (IS), Volume 36, Number 6, Pages 958-972, 2011. [code]

  64. Shumo Chu and James Cheng.
    Triangle Listing in Massive Networks and Its Applications.
    In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 672-680, 2011. (SIGKDD 2011)

  65. James Cheng, Yiping Ke, Shumo Chu, and M. Tamer Ozsu.
    Efficient Core Decomposition in Massive Networks.
    In Proceedings of the 27th IEEE International Conference on Data Engineering, Pages 51-62, 2011. (ICDE 2011)

  66. James Cheng, Yiping Ke, Ada Fu, Jeffrey Yu, and Linhong Zhu.
    Finding Maximal Cliques in Massive Networks by H*-Graph.
    In Proceedings of the 29th ACM SIGMOD International Conference on Management of Data, Pages 447-458, 2010. (SIGMOD 2010) [code]

  67. James Cheng, Ada Fu, and Jia Liu.
    K-Isomorphism: Privacy Preservation in Network Publication against Structural Attack.
    In Proceedings of the 29th ACM SIGMOD International Conference on Management of Data, Pages 459-470, 2010. (SIGMOD 2010)

  68. Changjiu Jin, Sourav Bhowmick, Xiaokui Xiao, James Cheng, and Byron Choi.
    GBLENDER: Towards Blending Visual Query Formulation and Query Processing in Graph Databases.
    In Proceedings of the 29th ACM SIGMOD International Conference on Management of Data, Pages 111-122, 2010. (SIGMOD 2010)

  69. James Cheng, Yiping Ke, and Wilfred Ng.
    Efficient Query Processing on Graph Databases.
    ACM Transactions on Database Systems (TODS), Volume 34, Number 1, Pages 2:1-2:48, 2009. [code] [GraphGen]

  70. Yiping Ke, James Cheng, and Jeffrey Yu.
    Efficient Discovery of Frequent Correlated Subgraph Pairs.
    In Proceedings of the 9th IEEE International Conference on Data Mining, Pages 239-248, 2009. (ICDM 2009)

  71. James Cheng, Yiping Ke, and Wilfred Ng.
    Efficient Processing of Group-Oriented Connection Queries in a Large Graph.
    In Proceedings of the 18th ACM Conference on Information and Knowledge Management, Pages 1481-1484, 2009. (CIKM 2009)

  72. Yiping Ke, James Cheng, and Jeffrey Xu Yu.
    Top-k Correlative Graph Mining.
    In Proceedings of the 9th SIAM International Conference on Data Mining, Pages 1038-1049, 2009. (SDM 2009)

  73. James Cheng, Yiping Ke, Wilfred Ng, and Jeffrey Xu Yu.
    Context-Aware Object Connection Discovery in Large Graphs.
    In Proceedings of the 25th International Conference on Data Engineering, Pages 856-867, 2009. (ICDE 2009)

  74. Yiping Ke, James Cheng, and Wilfred Ng.
    Correlated Pattern Mining in Quantitative Databases.
    ACM Transactions on Database Systems (TODS), Volume 33, Number 3, Pages 14:1-14:45, 2008.

  75. Yiping Ke, James Cheng, and Wilfred Ng.
    Efficient Correlation Search from Graph Databases.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 20, Number 12, Pages 1601-1615, 2008.

  76. James Cheng, Yiping Ke, and Wilfred Ng.
    Effective Elimination of Redundant Association Rules.
    Data Mining and Knowledge Discovery (DMKD/DAMI), Volume 16, Number 2, Pages 221-249, 2008.

  77. James Cheng, Yiping Ke, and Wilfred Ng.
    Maintaining Frequent Closed Itemsets over a Sliding Window.
    Journal of Intelligent Information Systems (JIIS), Volume 31, Number 3, Pages 191-215, 2008.

  78. James Cheng, Yiping Ke, and Wilfred Ng.
    A Survey on Algorithms for Mining Frequent Patterns over Data Streams.
    Knowledge and Information Systems Journal (KAIS), Volume 16, Number 1, Pages 1-27, 2008.

  79. Yiping Ke, James Cheng, and Wilfred Ng.
    An Information-Theoretic Approach to Quantitative Association Rule Mining.
    Knowledge and Information Systems Journal (KAIS), Volume 16, Number 2, Pages 213-244, 2008.

  80. James Cheng, Yiping Ke, Wilfred Ng, and An Lu.
    FG-Index: Towards Verification-Free Query Processing on Graph Databases.
    In Proceedings of the 26th ACM SIGMOD International Conference on Management of Data, Pages 857-872, 2007. (SIGMOD 2007) [code] [GraphGen]

  81. Yiping Ke, James Cheng, and Wilfred Ng.
    Correlation Search in Graph Databases.
    In Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Pages 390-399, 2007. (SIGKDD 2007)

  82. James Cheng and Wilfred Ng.
    A Development of Hash-Lookup Trees to Support Querying Streaming XML.
    In Proceedings of the 12th International Conference on Database Systems for Advanced Applications, Pages 768-780, 2007. (DASFAA 2007)

  83. Wilfred Ng and James Cheng.
    An Efficient Index Lattice for XML Query Evaluation.
    In Proceedings of the 12th International Conference on Database Systems for Advanced Applications, Pages 753-767, 2007. (DASFAA 2007)

  84. An Lu, Yiping Ke, James Cheng, and Wilfred Ng.
    Mining Vague Association Rules.
    In Proceedings of the 12th International Conference on Database Systems for Advanced Applications, Pages 891-897, 2007. (DASFAA 2007)

  85. James Cheng, Yiping Ke, and Wilfred Ng.
    δ-Tolerance Closed Frequent Itemsets.
    In Proceedings of the 6th IEEE International Conference on Data Mining, page 139-148, 2006. (ICDM 2006)

  86. Yiping Ke, James Cheng, and Wilfred Ng.
    Mining Quantitative Correlated Patterns Using an Information-Theoretic Approach .
    In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Pages 227-236, 2006. (SIGKDD 2006)

  87. James Cheng, Yiping Ke, and Wilfred Ng.
    Maintaining Frequent Itemsets over High-Speed Data Streams.
    In Proceedings of the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Pages 462-467, 2006. (PAKDD 2006) [ Technical Report ]

  88. Yiping Ke, James Cheng, and Wilfred Ng.
    MIC Framework: An Information-Theoretic Approach to Quantitative Association Rule Mining.
    In Proceedings of the 22nd International Conference on Data Engineering, page 112, 2006. (ICDE 2006)

  89. Yin Yang, Wilfred Ng, Ho Lam Lau, and James Cheng.
    An Efficient Approach to Support Querying Secure Outsourced XML Information.
    In Proceedings of the 18th Conference on Advanced Information Systems Engineering, Pages 157-171, 2006. (CAiSE 2006)

  90. Wilfred Ng, Yeung Wai Lam, and James Cheng.
    Comparative Analysis of XML Compression Technologies.
    World Wide Web Journal (WWWJ), Volume 9, Number 1, Pages 5-33, 2006.

  91. James Cheng and Wilfred Ng.
    XQzip: Querying Compressed XML Using Structural Indexing.
    In Proceedings of the 9th International Conference on Extending Database Technology, Pages 219-236, 2004. (EDBT 2004)

Tutorials

  1. Yiping Ke, James Cheng, and Jeffrey Xu Yu.
    Querying Large Graph Databases.
    In 15th International Conference on Database Systems for Advanced Applications, 2010. (DASFAA, 2010)

Book Chapters

  1. Fanhua Shang, Yuanyuan Liu, James Cheng, and Hong Cheng.
    Recovering Low-Rank and Sparse Matrices with Missing and Grossly Corrupted Observations.
    In T. Bouwmans, E. Zahzah, N. Aybat., Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing, CRC Press, Taylor and Francis Group, 2016.