activity
20132026
most citedCompressive Hyperspectral Imaging via Approximate Message Passing

93 citations · 331 across the 19 of their papers we have counts for

collaborators

19 papers

math.OC2026

ProxiCBO: A Provably Convergent Consensus-Based Method for Composite Optimization

Haoyu Zhang, Yanting Ma, Ruangrawee Kitichotkul +2

This paper introduces an interacting-particle optimization method tailored to possibly non-convex composite optimization problems, which arise widely in signal processing. The prop…

cs.IT2021

Multiview Sensing With Unknown Permutations: An Optimal Transport Approach

Yanting Ma, Petros T. Boufounos, Hassan Mansour +1

In several applications, including imaging of deformable objects while in motion, simultaneous localization and mapping, and unlabeled sensing, we encounter the problem of recoveri…

cs.IT2020

Local Convergence of an AMP Variant to the LASSO Solution in Finite Dimensions

Yanting Ma, Min Kang, Jack W. Silverstein +1

A common sparse linear regression formulation is the l1 regularized least squares, which is also known as least absolute shrinkage and selection operator (LASSO). Approximate messa…

eess.IV2020★ 4 cited

Two-Dimensional Non-Line-of-Sight Scene Estimation from a Single Edge Occluder

Sheila W. Seidel, John Murray-Bruce, Yanting Ma +3

Passive non-line-of-sight imaging methods are often faster and stealthier than their active counterparts, requiring less complex and costly equipment. However, many of these method…

math.OC2019★ 1 cited

On the modes of convergence of Stochastic Optimistic Mirror Descent (OMD) for saddle point problems

Yanting Ma, Shuchin Aeron, Hassan Mansour

In this article, we study the convergence of Mirror Descent (MD) and Optimistic Mirror Descent (OMD) for saddle point problems satisfying the notion of coherence as proposed in Mer…

cs.IT2019

Analysis of Approximate Message Passing with Non-Separable Denoisers and Markov Random Field Priors

Yanting Ma, Cynthia Rush, Dror Baron

Approximate message passing (AMP) is a class of low-complexity, scalable algorithms for solving high-dimensional linear regression tasks where one wishes to recover an unknown sign…