带噪观测的低秩矩阵补全：定量比较

Oct, 2009

带噪观测的低秩矩阵补全：定量比较

Low-rank Matrix Completion with Noisy Observations: a Quantitative Comparison

Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh

TL;DR本文围绕低秩矩阵重构问题，重点研究在观测样本受噪声污染时的矩阵填充问题，比较了OptSpace、ADMIRA和FPCA三种最新的填充算法在单一模拟平台上的性能，并给出了数值结果。实验表明，这些优秀的算法可以用于准确重构实际数据矩阵和随机生成的矩阵。

Abstract

We consider a problem of significant practical importance, namely, the reconstruction of a low-rank data matrix from a small subset of its entries. This problem appears in many areas such as collaborative filtering, com