69 citations · 119 across the 13 of their papers we have counts for
13 papers
Solving Quadratic Systems with Full-Rank Matrices Using Sparse or Generative Priors
Junren Chen, Michael K. Ng, Zhaoqiang Liu
The problem of recovering a signal from a quadratic system with full-rank ma…
Robust Quantitative Susceptibility Mapping via Approximate Message Passing with Parameter Estimation
Shuai Huang, James J. Lah, Jason W. Allen +1
Purpose: For quantitative susceptibility mapping (QSM), the lack of ground-truth in clinical settings makes it challenging to determine suitable parameters for the dipole inversion…
Orthogonal Matrix Retrieval with Spatial Consensus for 3D Unknown-View Tomography
Shuai Huang, Mona Zehni, Ivan Dokmanić +1
Unknown-view tomography (UVT) reconstructs a 3D density map from its 2D projections at unknown, random orientations. A line of work starting with Kam (1980) employs the method of m…
Approximate Message Passing with Parameter Estimation for Heavily Quantized Measurements
Shuai Huang, Deqiang Qiu, Trac D. Tran
Designing efficient sparse recovery algorithms that could handle noisy quantized measurements is important in a variety of applications -- from radar to source localization, spectr…
Fast Nonconvex Mapping Using ADMM
Shuai Huang, James J. Lah, Jason W. Allen +1
Magnetic resonance (MR)- mapping is widely used to study hemorrhage, calcification and iron deposition in various clinical applications, it provides a direct and precise map…
Bayesian Massive MIMO Channel Estimation with Parameter Estimation Using Low-Resolution ADCs
Shuai Huang, Deqiang Qiu, Trac D. Tran
In order to reduce hardware complexity and power consumption, massive multiple-input multiple-output (MIMO) systems employ low-resolution analog-to-digital converters (ADCs) to acq…
1-Bit Compressive Sensing via Approximate Message Passing with Built-in Parameter Estimation
Shuai Huang, Trac D. Tran
1-bit compressive sensing aims to recover sparse signals from quantized 1-bit measurements. Designing efficient approaches that could handle noisy 1-bit measurements is important i…
3D unknown view tomography via rotation invariants
Mona Zehni, Shuai Huang, Ivan Dokmanić +1
In this paper, we study the problem of reconstructing a 3D point source model from a set of 2D projections at unknown view angles. Our method obviates the need to recover the proje…
Solving Complex Quadratic Systems with Full-Rank Random Matrices
Shuai Huang, Sidharth Gupta, Ivan Dokmanić
We tackle the problem of recovering a complex signal from quadratic measurements of the form , where…
Geometric Invariants for Sparse Unknown View Tomography
Mona Zehni, Shuai Huang, Ivan Dokmanić +1
In this paper, we study a 2D tomography problem for point source models with random unknown view angles. Rather than recovering the projection angles, we reconstruct the model thro…
Reconstructing Point Sets from Distance Distributions
Shuai Huang, Ivan Dokmanić
We address the problem of reconstructing a set of points on a line or a loop from their unassigned noisy pairwise distances. When the points lie on a line, the problem is known as…
Sparse Signal Recovery via Generalized Entropy Functions Minimization
Shuai Huang, Trac D. Tran
Compressive sensing relies on the sparse prior imposed on the signal of interest to solve the ill-posed recovery problem in an under-determined linear system. The objective functio…
Sparse Signal Recovery using Generalized Approximate Message Passing with Built-in Parameter Estimation
Shuai Huang, Trac D. Tran
The generalized approximate message passing (GAMP) algorithm under the Bayesian setting shows advantage in recovering under-sampled sparse signals from corrupted observations. Comp…