Theory of Computing
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Title : The Gram--Schmidt Walk: A Cure for the Banaszczyk Blues
Authors : Nikhil Bansal, Daniel Dadush, Shashwat Garg, and Shachar Lovett
Volume : 15
Number : 21
Pages : 1-27
URL : http://www.theoryofcomputing.org/articles/v015a021
Abstract
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A classic result of Banaszczyk (Random Str. & Algor. 1997) states that
given any $n$ vectors in $\mathbb{R}^m$ with $\ell_2$-norm at most $1$
and any convex body $K$ in $\mathbb{R}^m$ of Gaussian measure at least
half, there exists a $\pm 1$ combination of these vectors that lies in
$5K$. Banaszczyk's proof of this result was non-constructive and it was
open how to find such a $\pm 1$ combination in polynomial time. In this
paper, we give an efficient randomized algorithm to find a $\pm 1$
combination of the vectors which lies in $cK$ for some fixed constant
$c> 0$. This leads to new efficient algorithms for several problems in
discrepancy theory.
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A conference version of this paper appeared in the Proceedings of the
50th ACM Symposium on Theory of Computing, 2018.