Title:	Support Vector Machines for Data Classification
Date:	December 12, 2005 (Monday)
Time:	10:30 a.m. - 11:30 a.m.
Venue:	Room 121, 1/F, Ho Sin-hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T.
Speaker:	Prof. Chih-Jen Lin Department of Computer Science National Taiwan University Taiwan

ABSTRACT:

Support vector machine (SVM) is a useful technique for data classification. In this talk I will

1. introduce its basic concepts, 2. discuss its current status, and 3. demonstrate its practical use.

Based on our experience of designing SVM software, I will also discuss some common mistakes made by users when applying SVM.

BIOGRAPHY:

Chih-Jen Lin received his Ph.D. from University of Michigan in 1998 and is currently an associate professor in the Department of Computer Science at National Taiwan University. His recent research focuses on support vector machines (SVM) for data classification and regression. His team is currently one of the major developers of SVM software, with thousands of users worldwide. He is also the winner of several international competitions on data classification/prediction such as IJCNN 2001, EUNITE 2001, and WCCI 2002. He serves as an associate editor of IEEE Transactions on Neural Networks.

Enquiries: Miss Temmy So at tel 2609 8444

For more information, please refer to http://www.cse.cuhk.edu.hk/seminar