The Gram-Schmidt walk: a cure for the Banaszczyk blues

N. Bansal, D. Dadush, S. Garg, Shachar Lovett
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引用次数: 60

Abstract

An important result in discrepancy due to Banaszczyk states that for any set of n vectors in ℝm of ℓ2 norm at most 1 and any convex body K in ℝm of Gaussian measure at least half, there exists a ± 1 combination of these vectors which lies in 5K. This result implies the best known bounds for several problems in discrepancy. Banaszczyk’s proof of this result is non-constructive and an open problem has been to give an efficient algorithm to find such a ± 1 combination of the vectors. In this paper, we resolve this question and give an efficient randomized algorithm to find a ± 1 combination of the vectors which lies in cK for c>0 an absolute constant. This leads to new efficient algorithms for several problems in discrepancy theory.
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克拉姆-施密特步法:治愈巴纳斯奇克忧郁
Banaszczyk关于差异的一个重要结果表明,对于任何一个n个向量的集合,在∈m中,≥2范数为1,并且在∈m中,任意一个凸体K≥一半的高斯测度,在5K中存在这些向量的±1组合。这一结果暗示了几个差异问题的已知界。Banaszczyk对这个结果的证明是非建设性的,一个开放的问题是给出一个有效的算法来找到这样一个向量的±1组合。在本文中,我们解决了这个问题,并给出了一个有效的随机化算法来求在cK中c>0为绝对常数的向量的±1组合。这导致了对差异理论中一些问题的新的有效算法。
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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