##### 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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