报告题目: Active Cost-sensitive Learning
报告人： Charles Ling, PhD
Department of Computer Science
University of Western Ontario
http://www.csd.uwo.ca/faculty/cling 报告时间：2007年7月4日上午10:00-11:00 报告地点：蒙民伟楼404会议室 摘要：
Most previous works of machine learning is "passive"; that is, the
learning program passively learns from the provided training examples.
Active learning, on the other hand, actively seeks for extra
information (effort) to improve learning (the gain). We unify the
effort and gain using cost, and study active learning in the
cost-sensitive framework. We propose various active learning algorithms
that can recognize the opportunity to "buy" extra information in order
to minimize the total cost (or maximize the net benefit). The extra
information includes missing attribute values, new examples, and new
class labels.
简历：
Professor Charles Ling earned his Msc and PhD from the Department of
Computer and Information Science at Univ of Pennsylvania in 1987 and
1989 respectively. Since then he has been a faculty member in Computer
Science at University of Western Ontario, Canada. His main research areas
include machine learning (theory,algorithms, and applications), and data minin
g.
He has published over 100 research papers in journals (such as Machine
Learning, JMLR, JAIR, Bioinformatics, IEEE TKDE, and Cognition)
and international conferences (such as IJCAI, AAAI, ICML, KDD, and
ICDM). He is an Associate Editor for IEEE TKDE, and IEEE Senior Member.
See http://www.csd.uwo.ca/faculty/cling for more info. |
