Jingrui He
Assistant professor in Computer Science Department at Stevens Institute of Technology
时间：2014 年 7 月 9 日上午 10:30-12:00
地点：张江校区软件楼 102 第二会议室
承办单位：复旦大学计算机科学技术学院
联系人：肖仰华 (shawyh@fudan.edu.cn)
Abstract:
Real-world applications exhibit rich heterogeneity, such as medical informatics, manufacturing, document classification, image classification/retrieval. In the past, researchers have mainly focused on modeling a single type of heterogeneity, such as task/view/instance/oracle heterogeneity. More recently, researchers have started to jointly model more than one type of heterogeneity, which has shown improved performance in the aforementioned applications. In this talk, I will introduce these techniques under the umbrella 'Heterogeneous Learning', which aims to address the rich heterogeneous properties in a target application. I will also discuss the application of these techniques in multiple domains, as well as future directions and key challenges.
Bio:
Dr. Jingrui He is currently an assistant professor in Computer Science Department at Stevens Institute of Technology. She received her M.Sc and Ph.D degree from Carnegie Mellon University in 2008 and 2010 respectively, both majored in Machine Learning. Her research interests include heterogeneous machine learning, rare category analysis, active learning and semi-supervised learning, with applications in social network analysis, semiconductor manufacturing, traffic analysis, etc. She has published over 40 referred articles and served as the organization committee member of ICML, KDD, etc.
