Expected Values Estimated via Mean-Field Approximation are 1/N-Accurate: Extended Abstract

Nicolas Gast
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引用次数: 7

Abstract

In this paper, we study the accuracy of mean-field approximation. We show that, under general conditions, the expectation of any performance functional converges at rate O(1/N) to its mean-field approximation. Our result applies for finite and infinite-dimensional mean-field models. We provide numerical experiments that demonstrate that this rate of convergence is tight.
通过平均场近似估计的期望值精度为1/ n:扩展摘要
本文研究了平均场近似的精度问题。我们证明,在一般条件下,任何性能泛函的期望以0 (1/N)的速率收敛到它的平均场近似。我们的结果适用于有限维和无限维平均场模型。我们提供了数值实验,证明了这种收敛速度是紧密的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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