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Oct, 2012
一种可扩展的CUR矩阵分解算法：更低的时间复杂度和更紧密的界限
A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound
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Shusen Wang, Zhihua Zhang, Jian Li
TL;DR
本文提出了一种新颖的随机CUR算法，该算法具有更紧的理论界限和较低的时间复杂度，并且可以避免在主内存中维护整个数据矩阵，实验结果表明其在多个真实世界数据集上相比现有的相对误差算法有显著提高。
Abstract
The
cur matrix decomposition
is an important extension of Nystr\"{o}m approximation to a general matrix. It approximates any
data matrix
in terms of a small number of its columns and rows. In this paper we propos
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