论文标题
矩阵完成，稀疏的嘈杂行
Matrix Completion with Sparse Noisy Rows
论文作者
论文摘要
在不同的潜在条件下，已经研究了精确的矩阵完成和低等级矩阵估计问题。在这项工作中，我们研究了在非分类噪声模型下确切的低级完成。在给定一些研究人员的情况下，许多研究人员以前已经研究了非分类的随机噪声模型，即噪声很少并且存在于某些列中。在本文中，我们假设每一行都可以接收随机噪声而不是列，并提出了一种对此噪声鲁棒的交互式算法。我们表明，当可以恢复基础矩阵并提出恢复基础矩阵的算法时，我们使用参数化技术来提供条件。
Exact matrix completion and low rank matrix estimation problems has been studied in different underlying conditions. In this work we study exact low-rank completion under non-degenerate noise model. Non-degenerate random noise model has been previously studied by many researchers under given condition that the noise is sparse and existing in some of the columns. In this paper, we assume that each row can receive random noise instead of columns and propose an interactive algorithm that is robust to this noise. We show that we use a parametrization technique to give a condition when the underlying matrix could be recoverable and suggest an algorithm which recovers the underlying matrix.
