Soo Mun Chong

Generalization Bounds for Semi-supervised Matrix Completion with Distributional Side Information

We study a matrix completion problem where both the ground truth R matrix and the unknown sampling distribution P over observed entries are low-rank matrices, and share a common subspace. We assume that a large amount M of unlabeled data drawn from the sampling distribution P is available, together