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Department of Computer Science Colloquium
2005 Series

Selective Ensemble

Prof. Zhi-Hua ZHOU
Nanjing University

Date: April 14, 2005 (Thursday)
Time: 11:30 am - 12:30 pm
Venue: SCT909, Cha Chi Ming Science Tower, Ho Sin Hang Campus

Ensemble learning is a machine learning paradigm where many learners are jointly used to solve a problem. In this talk, I will introduce the "selective ensemble" paradigm, which is based on the recognition of "many could be better than all". That is, when a set of learners are available, using some instead of all of them to make up an ensemble may be a better choice. Then, I will introduce an application of selective ensemble to face recognition, which will illustrate that selective ensemble is a general paradigm that can be used in many disciplines, not only limited to machine learning. The essence is that when there are many potential solutions to a problem, selecting and then combining some of them may be a good choice. In this talk I will also briefly introduce some applications of ensemble learning and some ongoing research of the LAMDA group of Nanjing University.

Prof. 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 a lecturer in 2001, and at present he is a professor, head of the LAMDA Group, and director of the AI Lab. He is also an adjunct professor of Nanjing University of Aeronautics and Astronautics, honorary fellow of Deakin University, Australia, and academic committee member of Shanghai Key Laboratory of Intelligent Information Processing at Fudan University. His research interests are in artificial intelligence, machine learning, data mining, pattern recognition, information retrieval, neural computing, and evolutionary computing. In these areas he has published over 40 He has won the Microsoft Fellowship Award (1999), the National Excellent Doctoral Dissertation Award of China (2003), and the Award of National Outstanding Youth Foundation of China (2003). He is an associate editor of Knowledge and Information Systems, editorial board member of Artificial Intelligence in Medicine, International Journal of Data Warehousing and Mining, Journal of Computer Science & Technology, Journal of Software, and reviewer for over twenty international journals including premium ones such as Artificial Intelligence and numerous IEEE Transactions. He is a grant review panelist for National Science Foundation of China (Information Science Division), and grant reviewer for Research Grants Council of Hong Kong and NWO-The Netherlands Organisation for Scientific Research. He served as the organising chair of the 7th Chinese Workshop on Machine Learning (2000), program co-chair of the 9th Chinese Conference on Machine Learning (2004), and program committee member of numerous international conferences. He is a senior member of the China Computer Federation (CCF), the vice chair of CCF Artificial Intelligence and Pattern Recognition Society, a councilor of Chinese Association of Artificial Intelligence (CAAI), the vice chair and chief secretary of CAAI Machine Learning Society, the vice chair of CAAI Rough Set and Soft Computing Society, and a member of IEEE and IEEE Computer Society.

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