Subject: Advances in Evolutionary Transfer Optimization
Speaker: Prof. Kay Chen Tan
Time: 15:00-16:00pm, 23rd Nov 2021
Place: https://meeting.tencent.com/dm/Tta7Xb9JgIDJ (Tencent Meeting ID: 743 347 993)
Abstract:
It is known that the processes of learning and the transfer of what has been learned are central to humans in problem-solving. However, the study of optimization methodology which learns from the problem solved and transfer what have been learned to help problem-solving on unseen problems, has been under-explored in the context of evolutionary computation. This talk will touch upon the topic of evolutionary transfer optimization (ETO), which focuses on knowledge learning and transfer across problems for enhanced evolutionary optimization performance. I will first present an overview of existing ETO approaches for problem-solving in evolutionary computation. I will then introduce our recent work on evolutionary multitasking for solving large-scale and dynamic multi-objective optimization problems by conducting evolutionary search concurrently on multiple search spaces corresponding to different optimization problems. It will end with a discussion on future ETO research directions, covering various topics ranging from theoretical analysis to real-world applications.
About the speaker:
Kay Chen Tan is currently a Chair Professor (Computational Intelligence) of the Department of Computing, The Hong Kong Polytechnic University. He has co-authored 7 books and published over 200 peer-reviewed journal articles. Prof. Tan is currently the Vice-President (Publications) of IEEE Computational Intelligence Society, USA. He was the Editor-in-Chief of IEEE Transactions on Evolutionary Computation from 2015-2020 (IF: 11.554) and IEEE Computational Intelligence Magazine from 2010-2013 (IF: 11.356). Prof. Tan currently serves as an Associate Editor of various international journals, such as IEEE Transactions on Artificial Intelligence, IEEE Transactions on Cybernetics, and IEEE Transactions on Games. Prof. Tan has been invited as a Plenary/Keynote speaker for many international conferences, including the 2020 IEEE World Congress on Computational Intelligence, the 2016 IEEE Symposium Series on Computational Intelligence, etc. He has served as an organizing committee Chair/Co-Chair for many international conferences, including the General Co-Chair of 2019 IEEE Congress on Evolutionary Computation, and the General Co-Chair of 2016 IEEE World Congress on Computational Intelligence, etc. Prof. Tan has received a number of research awards, such as the 2020 IEEE Transactions on Cybernetics Outstanding Paper Awards, the 2019 IEEE Computational Intelligence Magazine Outstanding Paper Awards, the 2016 IEEE Transactions on Neural Networks and Learning Systems Outstanding Paper Awards, the 2012 Outstanding Early Career Award presented by the IEEE Computational Intelligence Society. Prof. Tan is an IEEE Fellow, an IEEE Distinguished Lecturer Program (DLP) speaker since 2012, and an Honorary Professor at University of Nottingham in UK. He is also the Chief Co-Editor of Springer Book Series on Machine Learning: Foundations, Methodologies, and Applications since 2020.