Department machine learning talks: Transfer Learning with Applications

Title: Transfer Learning with Applications
Speaker: Prof. Qiang Yang, Hong Kong University of Science and Technology
Time: 11:15am, May 25 (Tue), 2010
Place: Room 210, CSIE Building

Abstract:

Transfer learning is a new machine learning and data mining framework that allows the training and test data to come from different distributions or feature spaces. We can find many novel applications of machine learning and data mining where transfer learning is necessary. In this talk, I will give an introduction to transfer learning and then highlight some important applications such as text and image classification, sensor network data mining and activity recognition, collaborative filtering and bioinformatics. I will also discuss some potential future directions of transfer learning.

Short Biography:

Qiang Yang is a professor of the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology. He is also an adjunct professor at Peking University, Beijing, and at Zhongshan University in Guangzhou, China. He received his PhD degree from the University of Maryland, College Park. His research interests include AI planning and sensor-based activity recognition, machine learning and case-based reasoning, and data mining. He is a senior member of the IEEE, the AAAI, and the ACM, and an associate editor for the IEEE Transactions on Knowledge and Data Engineering and IEEE Intelligent Systems, as well as the International Journal of Knowledge and Information Systems. More information about him can be found at http://www.cse.ust.hk/~qyang/