Home Sitemap Contact 中文 CAS
  • HOME
  • About Us
  • Research
  • People
  • International Cooperation
  • News
  • Education & Training
  • Join Us
  • Publications
  • Papers
  • Resources
  • Life at ICT
  • Links
  • Location:Home>News>Upcoming Events
    Cross-Domain Learning and Information Recommendation
    Update time: 2011-03-14
    Text Size: A A A
    Time:14:30 3-14-2011 

    Place: Meeting Hall, 4th Floor, ICT, CAS

    Due to the increasing ability for data collection and the increasing complexity of real-world problems, applications are facing the challenge of sharing information across multiple domains and multiple sources to achieve a common goal. Examples include collaborative filtering where rating matrices collect information from different user groups on items from different domains, and in semi-supervised learning where unlabeled samples are collected from domains different from the labeled instances. In this talk, I will address cross-domain learning from both collaborative filtering and semi-supervised learning perspectives. For collaborative filtering, we regard user rating matrices are generated from some hidden models, and our goal is to recover generative models hidden behind the rating matrices across different domains. For semi-supervised learning, we regard that both labeled and unlabeled samples are generated from some hidden concepts with labeling information partially observable for some samples. Our objective is to recover the hidden concepts, and take them as new features to link labeled and unlabeled samples for learning. Because unlabeled samples are only used to generate new features, but not to be explicitly included in the training set, our method overcomes the inherent disadvantages of the traditional methods, especially for samples not within the same domain as the labeled instances. Experimental results and comparisons demonstrate the performance of the proposed approach for cross-domain information sharing and recommendation. 

    He received his B.S. and M.S. degrees in Communication Engineering from Xidian University, and his PhD degree in Computer Science from Fudan University, Shanghai China, in 2001. He was a Postdoctoral Associate with the Department of Computer Science, Purdue University, West Lafayette, USA, from 2001 to 2002, a Research Assistant Professor with the Department of Computer Science, University of Vermont, USA, from 2002 to 2006, a tenure track Assistant Professor with the Department of Computer Science and Engineering, Florida Atlantic University, USA, from 2006 to 2009, and an Associate Professor at the Faculty of Engineering and Information Technology, University of Technology, Sydney, from 2009 to 2010. Since 2000, he has published more than 110 referred journal and conference proceeding papers.

    Address :No.6 Kexueyuan South Road Zhongguancun,Haidian District Beijing,China
    Postcode :100190 Tel : (8610)62601166 Email : office@ict.ac.cn