Institute of High Performance Computing

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People: Vibrant & Dynamic Culture

People

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Computing Science (CS)

Dr. WANG Yi

Dr. WANG Yi


Research Interests:

  • Reasoning, Planning, and Learning under Uncertainty
  • Graphical Models and Latent Variable Models
  • Bioinformatics and Business Analytics

Qualifications:

  • Ph.D., Computer Science, Hong Kong University of Science and Technology, 2009
  • B.Eng., Computer Science, University of Science and Technology of China, 2003

Published Journals/ Articles:

Journals

    • Zhiqiang Xu, Yiping Ke, Yi Wang, Hong Cheng, James Cheng (2014). GBAGC: A general Bayesian framework for attributed graph clustering. ACM Transactions on Knowledge Discovery from Data, in press.
    • Teng-Fei Liu, Nevin L. Zhang, Peixian Chen, April Hua Liu, Leonard K. M. Poon, Yi Wang (2013). Greedy learning of latent tree models for multidimensional clustering. Machine Learning, in press.
    • Yi Wang, Nevin L. Zhang, Tao Chen, Leonard K. M. Poon (2013). LTC: A latent tree approach to classification. International Journal of Approximate Reasoning, 54(4), 560-572.
    • Tao Chen, Nevin L. Zhang, Leonard K. M. Poon, Tengfei Liu, Yi Wang (2012). Model-based multidimensional clustering of categorical data. Artificial Intelligence, 176(1), 2246-2269.
    • Tianfang Wang, Nevin L. Zhang, Yan Zhao, Yi Wang, Xiuyan Wu, Shihong Yuan, Zhiyu Wang, Caifeng Du, Wenjie Xu, Chunguang Yu, Tao Chen, Kin Man Poon, Qingguo Wang (2009). Latent structure models and their application in TCM syndrome research. Journal of Beijing University of Traditional Chinese Medicine, 32(8), 519-526.
    • Yi Wang, Nevin L. Zhang, Tao Chen (2008). Latent tree models and approximate inference in Bayesian networks. Journal of Artificial Intelligence Research, 32, 879-900.
    • Nevin L. Zhang, Yi Wang, Tao Chen (2008). Discovery of latent structures: Experience with the CoIL challenge 2000 data set. Journal of Systems Science and Complexity, 21(2), 172-183.
    • Nevin L. Zhang, Shihong Yuan, Tao Chen, Yi Wang (2008). Latent tree models and diagnosis in traditional Chinese medicine. Artificial Intelligence in Medicine, 42(3), 229-245.
    • Nevin L. Zhang, Shihong Yuan, Tao Chen, Yi Wang (2008). Statistical validation of traditional Chinese medicine theories. Journal of Alternative and Complementary Medicine, 14(5), 583-587.
    • Shihong Yuan, Nevin L. Zhang, Tao Chen, Yi Wang (2008). Latent structure models and syndrome differentiation in traditional Chinese medicine (III): Model-based syndrome differentiation versus syndrome differentiation by experts. Journal of Beijing University of Chinese Medicine, 31(10), 659-663.
    • Nevin L. Zhang, Shihong Yuan, Yi Wang, Tao Chen (2008). Latent structure models and syndrome differentiation in traditional Chinese medicine (II): Analysis of kidney deficiency data. Journal of Beijing University of Chinese Medicine, 31(9), 584-587.

Conferences

    • Yi Wang, Kok Sung Won, David Hsu, Wee Sun Lee (2012). Monte Carlo Bayesian reinforcement learning. In Proceedings of the 29th International Conference on Machine Learning (ICML).
    • Zhiqiang Xu, Yiping Ke, Yi Wang, Hong Cheng, James Cheng (2012). A model-based approach to attributed graph clustering. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (SIGMOD), 505-516.
    • Geng Cui, Nevin L. Zhang and Yi Wang, (2012). Multidimensional Clustering Using Latent Feature Models for Consumer Segmentation and Forecasting. In Proceedings of the 4th Annual American Business Research Conference. Best Paper Award in Marketing
    • Tengfei Liu, Nevin L. Zhang, Kin Man Poon, Hua Liu, Yi Wang (2012). A novel LTM-based method for multi-partition clustering. In Proceedings of the 6th European Workshop on Probabilistic Graphical Models (PGM), 203-210.
    • Yi Wang, Nevin L. Zhang, Tao Chen, Leonard K. M. Poon (2011). Latent tree classifier. In Proceedings of the 11th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU), 410-421.
    • Tao Chen, Nevin L. Zhang, Yi Wang (2010). The role of operation granularity in search-based learning of latent tree models. In JSAI-isAI"10 Proceedings of the 2010 International Conference on New Frontiers in Artificial Intelligence, 219-231.
    • Leonard K. M. Poon, Nevin L. Zhang, Tao Chen, Tengfei Liu, Yi Wang (2010). Using Bayesian networks for model-based multiple clusterings: An example of exploratory analysis on NBA data. In the 1st International Workshop on Advanced Methodologies for Bayesian Networks (AMBN).
    • Leonard Poon, Nevin L. Zhang, Tao Chen, Yi Wang (2010). Variable selection in model-based clustering: To do or to facilitate. In Proceedings of the 27th International Conference on Machine Learning (ICML), 887-894.
    • Yi Wang, Nevin L. Zhang, Tao Chen (2008). Latent tree models and approximate inference in Bayesian networks. In Proceedings of the 23rd Conference on Artificial Intelligence (AAAI), 1112-1118.
    • Tao Chen, Nevin L. Zhang, Yi Wang (2008). Efficient model evaluation in the search-based approach to latent structure discovery. In Proceedings of the 4th European Workshop on Probabilistic Graphical Models (PGM), 57-64.
    • Nevin L. Zhang, Shihong Yuan, Tao Chen, Yi Wang (2007). Hierarchical latent class models and statistical foundation for traditional Chinese medicine. In Proceedings of the 11th Conference on Artificial Intelligence in Medicine (AIME), 139-143.
    • Yi Wang and Nevin L. Zhang (2006). Severity of local maxima for the EM algorithm: Experiences with hierarchical latent class models. In Proceedings of the 3rd European Workshop on Probabilistic Graphical Models (PGM), 301-308.

Professional Services

    Conference Senior PC Member

    • Conference on Uncertainty in Artificial Intelligence (UAI) 2014

    Conference PC Member

    • Conference on Uncertainty in Artificial Intelligence (UAI) 2010, 2011, 2012, 2013
    • International Joint Conference on Artificial Intelligence (IJCAI) 2011, 2013
    • International Workshop on Advanced Methodologies for Bayesian Networks (AMBN) 2010

    Journal Referee

    • International Journal of Approximate Reasoning
    • Machine Learning Journal
    • Neurocomputing
    • Pattern Recognition

This page is last updated at: 10-MAR-2014