From Supervised Learning to Transfer Learning
|Title:||From Supervised Learning to Transfer Learning|
|Date:||May 23, 2019 (Thursday)|
|Time:||11:00 am - 12:00 pm|
|Venue:||Room 121, 1/F, Ho Sin-Hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T.|
|Speaker:|| Dr. Sinno Jialin PAN
Provost's Chair Associate Professor
Nanyang Technological University
Recently, supervised-learning algorithms such as deep learning models have made a great impact on our society, but it has become clear that they also have important limitations. First, the learning of supervised models relies heavily on the size and quality of the annotated training data. However, in many real-world applications, there is a serious lack of annotation, making it impossible to obtain high-quality models. Second, models trained by many of today’s supervised-learning algorithms are domain specific, causing them to perform poorly when the domains change. Transfer learning is a promising technique to address the aforementioned limitations of supervised learning. In this talk, I will present what I have done on transfer learning and my current research focuses.
Dr Sinno Jialin Pan is a Provost's Chair Associate Professor with the School of Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. He received his Ph.D. degree in computer science from the Hong Kong University of Science and Technology (HKUST) in 2011. Prior to joining NTU as a Nanyang Assistant Professor (university's elite assistant professorship), he was a scientist and Lab Head of text analytics with the Data Analytics Department, Institute for Infocomm Research, Singapore from Nov. 2010 to Nov. 2014. He was named to "AI 10 to Watch" by the IEEE Intelligent Systems magazine in 2018. His research interests include transfer learning, and its applications to wireless-sensor-based data mining, text mining, sentiment analysis, and software engineering.
Enquiries: Ms. Shirley Lau at tel. 3943 8439
For more information, please refer to http://www.cse.cuhk.edu.hk/en/events