arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2207.06271cs.ITcs.CRcs.NAmath.ITmath.NA
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安全的线性MDS编码矩阵求逆

Secure Linear MDS Coded Matrix Inversion

Neophytos Charalambides, Mert Pilanci, Alfred Hero

摘要:

在许多科学领域中,求大型满秩矩阵的逆是一项繁琐的运算。在本文中,我们提出了一个编码计算方法恢复矩阵逆近似。我们首先提出了一个近似矩阵求逆算法,它不需要矩阵分解,但使用黑盒最小二乘优化求解器作为子程序,给出一个真正的满秩矩阵的逆的估计。然后,我们提出了一个分布式框架,我们的算法可以实现,并展示了我们如何利用稀疏平衡MDS生成矩阵设计矩阵求逆编码计算方案。我们专注于平衡的里德-所罗门码,这是最佳的计算负载方面,从工人到主服务器的通信。我们还讨论了我们的算法可以用来计算一个满秩矩阵的伪逆,以及如何从窃听者的通信是安全的。

英文摘要:

A cumbersome operation in many scientific fields, is inverting large full-rank matrices. In this paper, we propose a coded computing approach for recovering matrix inverse approximations. We first present an approximate matrix inversion algorithm which does not require a matrix factorization, but uses a black-box least squares optimization solver as a subroutine, to give an estimate of the inverse of a real full-rank matrix. We then present a distributed framework for which our algorithm can be implemented, and show how we can leverage sparsest-balanced MDS generator matrices to devise matrix inversion coded computing schemes. We focus on balanced Reed-Solomon codes, which are optimal in terms of computational load; and communication from the workers to the master server. We also discuss how our algorithms can be used to compute the pseudoinverse of a full-rank matrix, and how the communication is secured from eavesdroppers.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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