IEEE Computational Intelligence Society Distinguished Lecturer - Non-Iterative Learning Methods for Classification and Forecasting

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This talk will first introduce the main non-iterative learning paradigms such as the randomization based feedforward neural networks, random forest, extreme learning machines and kernel ridge regression. The talk will also consider computational complexity with increasing scale of the classification/forecasting problems. The talk will also present extensive benchmarking studies on ensemble realization of these methods using classification and forecasting datasets.



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  • University of Technology Sydney
  • Sydney, New South Wales
  • Australia 2000
  • Building: Building 10, Level 02
  • Room Number: 340

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  Speakers

PN Suganthan of Nanyang Technological University

Topic:

Non-Iterative Learning Methods for Classification and Forecasting

This talk will first introduce the main non-iterative learning paradigms such as the randomization based feedforward neural networks, random forest, extreme learning machines and kernel ridge regression. The talk will also consider computational complexity with increasing scale of the classification/forecasting problems. The talk will also present extensive benchmarking studies on ensemble realization of these methods using classification and forecasting datasets

Biography:

Ponnuthurai Nagaratnam Suganthan is Fellow of the Institute of Electrical and Electronics Engineers for contributions to optimization using evolutionary and swarm algorithms.

His research interests include swarm and evolutionary algorithms, pattern recognition, forecasting, randomized neural networks, deep learning and applications of the swarm, evolutionary & machine learning algorithms. His publications have been well cited (Google scholar: more than 29k). His SCI indexed publications attracted over 1000 SCI citations in each calendar years 2013, 2014, 2015, 2016 and 2017. He was selected as one of the highly cited researchers by Thomson Reuters in 2015, 2016 , and 2017 in computer science.

He received the B.A degree, Postgraduate Certificate and M.A degree in Electrical and Information Engineering from the University of Cambridge, UK. After completing his Ph.D. research in 1995, he served as a pre-doctoral Research Assistant in the Dept of Electrical Engineering, University of Sydney in 1995–96 and a lecturer in the Dept of Computer Science and Electrical Engineering, University of Queensland in 1996–99. He moved to NTU in 1999. He is an Editorial Board Member of the Evolutionary Computation Journal, MIT Press. He is an associate editor of the Applied Soft Computing (2018-), IEEE Trans on Cybernetics (2012 - ), IEEE Trans on Evolutionary Computation (2005 -), Information Sciences (Elsevier) (2009 - ), Pattern Recognition (Elsevier) (2001 - ) and Int. J. of Swarm Intelligence Research (2009 - ) Journals. He is a founding co-editor-in-chief of Swarm and Evolutionary Computation (2010 - ), an SCI Indexed Elsevier Journal. His co-authored SaDE paper (published in April 2009) won the "IEEE Trans. on Evolutionary Computation outstanding paper award" in 2012. His former Ph.D. student, Dr Jane Jing Liang, won the IEEE CIS Outstanding Ph.D. dissertation award, in 2014. IEEE CIS Singapore Chapter won the best chapter award in Singapore in 2014 for its achievements in 2013 under his leadership. He served as the General Chair of the IEEE SSCI 2013. He has been a member of the IEEE (S'90, M'92, SM'00, Fellow’15) since 1990 and an elected AdCom member of the IEEE Computational Intelligence Society (CIS) in 2014-2016.