IEEE CIS Virtual Seminar: Hypervolume Approximation for Many-objective Optimization
IEEE Computational Intelligence Society, Australian Capital Territory (ACT) chapter invites you to:
Virtual Seminar - 24 August 2022, 3.30-4.30 pm AEST (Canberra time)
Speaker: Dr. Ke Shang, Southern University of Science and Technology (SUSTech), Shenzhen, China
Title: Hypervolume Approximation for Many-objective Optimization
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Abstract: Hypervolume is one of the most popular performance indicators
in evolutionary multi-objective optimization (EMO). It possesses rich
theoretical properties and has been extensively used for performance
evaluation and algorithm design. However, its main drawback is that it
becomes computationally intractable in high-dimensional spaces, which
limited its application in many-objective optimization. In order to overcome
this difficulty, approximation methods can be used instead of exact methods
for hypervolume calculation. In this talk, I will first review studies on
hypervolume approximation in the literature. Then I will present our recent
work on hypervolume approximation and its applications including EMO
algorithm design and subset selection. Lastly, I will give some directions for
future research.
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Speaker biography:
Dr. Ke Shang received his BS and PhD
degrees from Xi’an Jiaotong University, China, in 2009 and
2016, respectively. He was a Visiting Scholar in Tokushima
University, Japan, from 2012 to 2014. He is currently a
Research Assistant Professor in Southern University of
Science and Technology, China. His research interests
include multiobjective optimization and artificial
intelligence. He received Best Paper Awards from GECCO
2018 and 2021, First Runner-up Conference Paper Award from CEC 2019,
and Best Paper Nomination from PPSN 2020. He is the organizer of
“Workshop on Subset Selection in Evolutionary Multi-objective
Optimization” at WCCI 2022, and two tutorials at WCCI 2022 and GECCO
2022. He is a member of IEEE. For more information, please visit
https://cse.sustech.edu.cn/faculty/~shangk/.
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Speakers
Dr Ke Shang
Hypervolume Approximation for Many-objective Optimization
Address:Shenzhen, China
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