##### Department of Mathematics,

University of California San Diego

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### Math 278C: Optimization and Data Science

## Prof. Yuhua Zhu

#### UCSD

## An interacting particle method for global optimization

##### Abstract:

This talk presents a particle-based optimization method designed for addressing global optimization problems, particularly in cases where the loss function exhibits non-differentiability or non-convexity. Numerically, we show that it outperforms gradient-based method in finding global optimizer. Theoretically, A rigorous mean-field limit of the particle system is derived, and the convergence of the mean-field limit to the global minimizer is established. In addition, we will talk about its application to the constrained optimization problems and federated learning.

Host: Jiawang Nie

### April 24, 2024

### 4:00 PM

APM 7321

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