View article

For entry sensing in matrix recovery (also known as matrix completion), we show that with high probability the Riemannian gradient descent and conjugate gradient descent methods based on the low rank matrix manifold are guaranteed to converge to the measured rank r matrix X∈ Rn× n provided r≤ C· σ2 min (X) σ2 max (X)