activity
20072026
most citedGlobal Optimality in Low-rank Matrix Optimization

128 citations · 738 across the 58 of their papers we have counts for

collaborators
Showing 2016 · cs.ITShow all

8 papers · 2 filters

cs.IT2016

Randomized Learning of the Second-Moment Matrix of a Smooth Function

Armin Eftekhari, Michael B. Wakin, Ping Li +1

Consider an open set , equipped with a probability measure . An important characteristic of a smooth function $f:\mathbb{D}\rightarrow\mathbb{R}…

cs.IT2016

Weighted Matrix Completion and Recovery with Prior Subspace Information

Armin Eftekhari, Dehui Yang, Michael B. Wakin

An incoherent low-rank matrix can be efficiently reconstructed after observing a few of its entries at random, and then solving a convex program that minimizes the nuclear norm. In…

cs.IT2016★ 2 cited

Streaming Principal Component Analysis From Incomplete Data

Armin Eftekhari, Gregory Ongie, Laura Balzano +1

Linear subspace models are pervasive in computational sciences and particularly used for large datasets which are often incomplete due to privacy issues or sampling constraints. Th…

cs.IT2016★ 3 cited

What to Expect When You Are Expecting on the Grassmannian

Armin Eftekhari, Laura Balzano, Michael B. Wakin

Consider an incoming sequence of vectors, all belonging to an unknown subspace , and each with many missing entries. In order to estimate , it i…

cs.IT2016

MC^2: A Two-Phase Algorithm for Leveraged Matrix Completion

Armin Eftekhari, Michael B. Wakin, Rachel A. Ward

Leverage scores, loosely speaking, reflect the importance of the rows and columns of a matrix. Ideally, given the leverage scores of a rank- matrix ,…

cs.IT2016

On the Asymptotic Equivalence of Circulant and Toeplitz Matrices

Zhihui Zhu, Michael B. Wakin

Any sequence of uniformly bounded Hermitian Toeplitz matrices is asymptotically equivalent to a certain sequence of circulant matrice…