Bypassing KLS: Gaussian Cooling and an O^*(n3) Volume Algorithm

Benjamin R. Cousins, S. Vempala
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引用次数: 54

Abstract

We present an O*(n3) randomized algorithm for estimating the volume of a well-rounded convex body given by a membership oracle, improving on the previous best complexity of O*(n4). The new algorithmic ingredient is an accelerated cooling schedule where the rate of cooling increases with the temperature. Previously, the known approach for potentially achieving such complexity relied on a positive resolution of the KLS hyperplane conjecture, a central open problem in convex geometry.
绕过KLS:高斯冷却和O^*(n3)体积算法
我们提出了一种O*(n3)随机算法,用于估计由隶属度表给出的圆角凸体的体积,改进了之前的最佳复杂度O*(n4)。新的算法成分是一个加速冷却计划,冷却速度随着温度的升高而增加。以前,已知的实现这种复杂性的方法依赖于KLS超平面猜想的正解,KLS超平面猜想是凸几何中的一个中心开放问题。
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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