Low-rank matrix approximation in the infinity norm

被引:9
|
作者
Gillis, Nicolas [1 ]
Shitov, Yaroslav [2 ]
机构
[1] Univ Mons, Fac Polytech, Dept Math & Operat Res, Rue Houdain 9, B-7000 Mons, Belgium
[2] Natl Res Univ Higher Sch Econ, 20 Myasnitskaya Ulitsa, Moscow 101000, Russia
基金
俄罗斯科学基金会; 欧洲研究理事会;
关键词
Low-rank matrix approximations; l(infinity) norm; Computational complexity; PCA;
D O I
10.1016/j.laa.2019.07.017
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The low-rank matrix approximation problem with respect to the entry-wise l(infinity)-norm is the following: given a matrix M and a factorization rank r, find a matrix X whose rank is at most r and that minimizes max(i,j) vertical bar M-i,M-j - X-ij vertical bar. In this paper, we prove that the decision variant of this problem for r = 1 is NP-complete using a reduction from the problem 'not all equal 3SAT'. We also analyze several cases when the problem can be solved in polynomial time, and propose a simple practical heuristic algorithm which we apply on the problem of the recovery of a quantized low-rank matrix, that is, to the problem of recovering a low-rank matrix whose entries have been rounded up to some accuracy. (C) 2019 Elsevier Inc. All rights reserved.
引用
收藏
页码:367 / 382
页数:16
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