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Tutorials: Nov 13, 2011, Shanghai, China
Main Conference: Nov 14-17, 2011, Shanghai, China
Workshops: Nov 18, 2011, Hangzhou, China
 
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   Final program of ICONIP2011 and book of abstracts are available now.  
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Special Session on Advances in Statistical Relational Learning

Organizers:

Dr. Wu-Jun Li
Shanghai Jiao Tong University, China
E-mail: liwujun@cs.sjtu.edu.cn


Prof. Dit-Yan Yeung
Hong Kong University of Science and Technology, Hong Kong, China
E-mail: dyyeung@cse.ust.hk


Description:

Recent years have witnessed a proliferation of relational data which widely exist in a large variety of application areas, such as web mining, social network analysis, bioinformatics, economics and marketing. Statistical relational learning (SRL), which attempts to perform learning and inference in domains with complex relational structures, has recently become an emerging research area. On one hand, SRL is much more challenging than traditional machine learning due to the complex relationships (or interactions) between instances in relational data. On the other hand, the richer information in relational data will also provide opportunities for SRL researchers to design novel learning models and algorithms.

Topics of interest include but are not limited to:

  1. Learning theory and models
    • Statistical relational learning theory
    • Statistical relational learning models
  2. Applications
    • Social media mining
    • Collaborative filtering and recommender systems
    • Social network analysis and graph mining
    • Biological network modeling
    • Epidemic modeling
    • Network-based marketing
Biographies:

        Dr. Wu-Jun Li is an assistant professor in the Department of Computer Science and Engineering at Shanghai Jiao Tong University, China. He received his Ph.D. degree in Computer Science from the Hong Kong University of Science and Technology in 2010. His research interests are in statistical machine learning, pattern recognition and data mining. More information about him can be found at: http://www.cs.sjtu.edu.cn/~liwujun.


        Prof. Dit-Yan Yeung is a professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology, Hong Kong, China. He received his Ph.D. degree in Computer Science from the University of Southern California. He started his academic career as an Assistant Professor at the Illinois Institute of Technology. He then joined the Hong Kong University of Science and Technology. His research interests are in computational and statistical approaches to machine learning, pattern recognition and data mining. More information about him can be found at: http://www.cse.ust.hk/~dyyeung.


 
         
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