Zhi-Hua Zhou,
Nanjing University, China


Title: Ensemble and Semi-Supervised - Single or Combine

 

Abstract: Ensemble learning and semi-supervised learning are two different machine learning paradigms. They have almost the same goal, that is, to attain a strong generalization. Both paradigms have achieved great success during the past decade, however, they are almost separately developed since they have different cultures. Ensemble learning attempts to achieve strong generalization by using multiple learners; semi-supervised learning attempts to achieve strong generalization by exploiting unlabeled data. In this talk, we will give introduction to ensemble learning and semi-supervised learning, and discuss on why they can be helpful to each other.


Bio Sketch: Zhi-Hua Zhou received his B.Sc., M.Sc. and Ph.D. degrees in computer science from Nanjing University, China, in 1996, 1998 and 2000, respectively, all with the highest honor. He joined the Department of Computer Science & Technology of Nanjing University as an assistant professor in 2001, and at present he is Cheung Kong professor and founding director of the LAMDA Group. He has wide research interests, mainly including artificial intelligence, machine learning, data mining, information retrieval and pattern recognition. In these areas he has published over 70 papers in leading journals and conferences. He has won various awards or honors. He is an associate editor-in-chief of Chinese Science Bulletin, associate editor of IEEE Transactions on Knowledge and Data Engineering, and on the editorial boards of Artificial Intelligence in Medicine, Intelligent Data Analysis, Science in China, etc. He is/was Steering Committee member of PAKDD and PRICAI, program committee chair/co-chair of PAKDD'07, PRICAI'08, ACML'09, vice chair or area chair of conferences including IEEE ICDM'06, IEEE ICDM'08, SIAM DM'09, ACM CIKM'09, etc., and chaired a dozen of native conferences. He is the chair of the Machine Learning Society of the Chinese Association of Artificial Intelligence (CAAI), vice chair of the Artificial Intelligence & Pattern Recognition Society of the China Computer Federation (CCF) and chair of the IEEE Computer Society Nanjing Chapter.