Advances in Co-training Style Semi-supervised Learning

Speaker:  Professor Zhi-Hua ZHOU
	  LAMDA Group
	  National Key Laboratory for Novel Software Technology
	  Nanjing University

Title:	"Advances in Co-training Style Semi-supervised Learning"

Date:	Tuesday, 11 March 2008

Time:	1:30pm - 2:30pm

Venue:	Room 2404 (via lifts 17/18)
	HKUST

Abstract:

Traditional supervised learning approaches require a lot of labelled
training examples to achieve a strong generalization ability. In many
machine learning and data mining applications, however, it is relatively
easy to collect a large amount of unlabeled data yet rather expensive to
get a large amount of labeled data since labeling the examples requires
human effort. Semi-supervised learning attempts to exploit unlabeled data
to help improve the learning performance. In this talk, I will briefly
introduce some of our results in research of co-training style
semi-supervised learning

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Biography:

Zhi-Hua Zhou is currently Cheung Kong Professor and Head of the LAMDA
group affiliated with both the Department of Computer Science & Technology
and the National Key Laboratory for Novel Software Technology at Nanjing
University. He has wide research interests, mainly including artificial
intelligence, machine learning, data mining, information retrieval and
pattern recognition. In these areas he has published over 50 papers in
leading journals and conferences. He is on the editorial boards of
journals including Artificial Intelligence in Medicine, Intelligent Data
Analysis, Knowledge and Information Systems, etc., and served as guest
editor/co-editor for journals including ACM/Springer Multimedia Systems,
The Computer Journal, etc. He is/was a steering committee member of PAKDD,
program committee chair/co-chair of PAKDD'07 and PRICAI'08, vice chair of
IEEE ICDM'06, ICDM'08, etc., program committee member of many conferences
including AAAI, ICML, ECML, ACM SIGKDD, IEEE ICDM, ACM Multimedia, etc.,
and general chair/co-chair or program committee chair/co-chair of over ten
national conferences. He is the chair of the CAAI Machine Learning
Society, vice chair of the CCF Artificial Intelligence & Pattern
Recognition Society and chair of IEEE Computer Society Nanjing Chapter.