We propose two graph matrix completion algorithms called GMCM-DL and GMCR-DL, by employing a new definition of Graph Total Variation for matrices based on the directed Laplacian Matrix. We show that these algorithms outperform their peers in terms of RMSEs for both cases of uniform and row observations.

中文翻译：

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基于有向拉普拉斯矩阵的图总变异图的矩阵完成

通过基于有向拉普拉斯矩阵对矩阵采用图总变化的新定义，我们提出了两种称为GMCM-DL和GMCR-DL的图矩阵完成算法。我们显示，就均匀观测和行观测而言，这些算法在RMSE方面均优于同类算法。