Here, we prove Theorem 1 of the paper “Two-snapshot DOA Estimation via Hankel-
structured Matrix Completion”. For the sake of completeness. Let y∈ Cn be the ground-truth …

Matrix (or operator) recovery from linear measurements is a well-studied problem. However,
there are situations where only bilinear or quadratic measurements are available. A bilinear …

This paper presents several novel theoretical results regarding the recovery of a low-rank
matrix from just a few measurements consisting of linear combinations of the matrix entries …

In this paper, we develop a theory of matrix completion for the extreme case of noisy 1-bit
observations. Instead of observing a subset of the real-valued entries of a matrix M, we …

In this paper, we consider low rank matrix estimation using either matrix-version Dantzig
Selector $\hat {A} _ {\lambda}^ d $ or matrix-version LASSO estimator $\hat {A} _ {\lambda} …

In this paper, we study the problem of estimating the direction of arrival (DOA) using a
sparsely sampled uniform linear array (ULA). Based on an initial incomplete ULA …

We consider the problem of recovering a low-rank matrix M from a small number of random
linear measurements. A popular and useful example of this problem is matrix completion, in …

We study low rank matrix recovery from undersampled measurements via nuclear norm
minimization. We aim to recover an n 1 xn 2 matrix X from m measurements (Frobenius inner …

In matrix recovery from random linear measurements, one is interested in recovering an
unknown M-by-N matrix X 0 from n< MN measurements yi= T r (A i⊤ X 0), where each A i is …

In this paper, we develop a theory of matrix completion for the extreme case of noisy 1-bit
observations. Instead of observing a subset of the real-valued entries of a matrix M, we …