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
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