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比利时vs摩洛哥足彩 ,
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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