Department of Mathematics,
University of California San Diego
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Math 278C: Optimization and Data Science
Dr. Jie Wang
Chinese Academy of Sciences
Structured Polynomial Optimization
Abstract:
Polynomial optimization is an important class of non-convex optimization problems, and has a powerful modelling ability for both continuous and discrete optimization. Over the past two decades, the moment-SOS hierarchy has been well developed for globally solving polynomial optimization problems. However, the rapidly growing size of SDP relaxations arising from the moment-SOS hierarchy makes it computationally intractable for large-scale problems. In this talk, I will show that there are plenty of algebraic structures to be exploited to remarkably improve the scalability of the moment-SOS hierarchy, which leads to the new active research area of structured polynomial optimization.
Host: Jiawang Nie
October 18, 2023
3:00 PM
APM 7321
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