学术报告:From Supervised Learning to Transfer Learning

题目:From Supervised Learning to Transfer Learning

主讲人:潘嘉林(Sinno Jialin Pan)新加坡南洋理工大学  助理教授

日期:2018年12月12日(星期三)

时间:16:00 - 17:30

地点:数据科学与计算机学院 A101

主持:郑伟诗 教授

摘要:

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 we have done on transfer learning and our current research focuses.

个人介绍:

Sinno Jialin Pan is a Nanyang Assistant Professor at the School of Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. He is also a Cluster Deputy Director of the Data Science and AI Center at NTU. Prior to joining NTU, he was a scientist and Lab Head of text analytics with the Data Analytics Department at Institute for Infocomm Research, A*STAR, Singapore.