most citedCompressed Sensing of Simultaneous Low-Rank and Joint-Sparse Matrices

32 citations · 39 across the 6 of their papers we have counts for

collaborators

6 papers

math.OC2017

Structure-Adaptive, Variance-Reduced, and Accelerated Stochastic Optimization

Junqi Tang, Francis Bach, Mohammad Golbabaee +1

In this work we explore the fundamental structure-adaptiveness of state of the art randomized first order algorithms on regularized empirical risk minimization tasks, where the sol…

math.OC20171 cited

Exploiting the Structure via Sketched Gradient Algorithms

Junqi Tang, Mohammad Golbabaee, Mike Davies

Sketched gradient algorithms have been recently introduced for efficiently solving the large-scale constrained Least-squares regressions. In this paper we provide novel convergence…

cs.IT20171 cited

Inexact Gradient Projection and Fast Data Driven Compressed Sensing

Mohammad Golbabaee, Mike E. Davies

We study convergence of the iterative projected gradient (IPG) algorithm for arbitrary (possibly nonconvex) sets and when both the gradient and projection oracles are computed appr…

cs.OH2017

Insense: Incoherent Sensor Selection for Sparse Signals

Amirali Aghazadeh, Mohammad Golbabaee, Andrew S. Lan +1

Sensor selection refers to the problem of intelligently selecting a small subset of a collection of available sensors to reduce the sensing cost while preserving signal acquisition…

cs.IT201232 cited

Compressed Sensing of Simultaneous Low-Rank and Joint-Sparse Matrices

Mohammad Golbabaee, Pierre Vandergheynst

In this paper we consider the problem of recovering a high dimensional data matrix from a set of incomplete and noisy linear measurements. We introduce a new model that can efficie…

cs.LG20125 cited

Structured Sparsity Models for Multiparty Speech Recovery from Reverberant Recordings

Afsaneh Asaei, Mohammad Golbabaee, Hervé Bourlard +1

We tackle the multi-party speech recovery problem through modeling the acoustic of the reverberant chambers. Our approach exploits structured sparsity models to perform room modeli…