Matrix Completion under Low-Rank Missing Mechanism

@article{Mao2018MatrixCU,
title={Matrix Completion under Low-Rank Missing Mechanism},
author={Xiaojun Mao and Raymond K. W. Wong and S. Chen},
journal={ArXiv},
year={2018},
volume={abs/1812.07813}
}

Matrix completion is a modern missing data problem where both the missing structure and the underlying parameter are high dimensional. Although missing structure is a key component to any missing data problems, existing matrix completion methods often assume a simple uniform missing mechanism. In this work, we study matrix completion from corrupted data under a novel low-rank missing mechanism. The probability matrix of observation is estimated via a high dimensional low-rank matrix estimation… CONTINUE READING