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Department of Computer Science Colloquium
2016 Series

Multi-objective Ensemble Learning and its Applications

Prof. Xin Yao
University of Birmingham

Date: January 26, 2016 (Tuesday)
Time: 4:00 - 5:00 pm
Venue: RRS905, Sir Run Run Shaw Building, Ho Sin Hang Campus

This talk introduces some basic ideas of multi-objective learning and the importance of diversity in ensemble learning. It describes a number of ensemble learning algorithms for online learning, class imbalance learning, and online class imbalance learning. The role of diversity in such ensemble learning algorithms are investigated and exploited to develop better algorithms. Applications of such algorithms in software engineering, especially in software effort estimation and software defect prediction, are described. Our experimental results show that multi-objective ensemble learning can provide a very good alternative to other learning paradigms and can produce excellent results for practical problems. Finally, some future research directions are discussed.

Xin Yao is a Professor of Computer Science and the Director of CERCIA (Centre of Excellence for Research in Computational Intelligence and Applications) at the University of Birmingham, UK. He is an IEEE Fellow and a Distinguished Lecturer of IEEE Computational Intelligence Society (CIS).

His work won the 2001 IEEE Donald G. Fink Prize Paper Award, 2010 and 2015 IEEE Transactions on Evolutionary Computation Outstanding Paper Awards, 2010 BT Gordon Radley Award for Best Author of Innovation (Finalist), 2011 IEEE Transactions on Neural Networks Outstanding Paper Award, and many other best paper awards. He won the prestigious Royal Society Wolfson Research Merit Award in 2012 and the 2013 IEEE CIS Evolutionary Computation Pioneer Award. He was the Editor-in-Chief (2003-08) of IEEE Transactions on Evolutionary Computation and the Immediate Past President (2016) of IEEE CIS. His major research interests include evolutionary computation, ensemble learning, and their applications, especially in software engineering.

********* ALL INTERESTED ARE WELCOME ***********
(For enquiry, please contact Computer Science Department at 3411 2385)
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