activity
20172020
most citedA Theoretical Analysis of Sparse Recovery Stability of Dantzig Selector and LASSO

3 citations · 4 across the 4 of their papers we have counts for

collaborators

8 papers

eess.SP20201 cited

Improved RIP-Based Bounds for Guaranteed Performance of two Compressed Sensing Algorithms

Yun-Bin Zhao, Zhi-Quan Luo

Iterative hard thresholding (IHT) and compressive sampling matching pursuit (CoSaMP) are two types of mainstream compressed sensing algorithms using hard thresholding operators for…

math.OC2020

Dual-density-based reweighted -algorithms for a class of -minimization problems

Jialiang Xu, Yun-Bin Zhao

The optimization problem with sparsity arises in many areas of science and engineering such as compressed sensing, image processing, statistical learning and data sparse approximat…

math.OC2020

Newton-Step-Based Hard Thresholding Algorithms for Sparse Signal Recovery

Nan Meng, Yun-Bin Zhao

Sparse signal recovery or compressed sensing can be formulated as certain sparse optimization problems. The classic optimization theory indicates that the Newton-like method often…

math.OC2019

Analysis of Optimal Thresholding Algorithms for Compressed Sensing

Yun-Bin Zhao, Zhi-Quan Luo

The optimal -thresholding (OT) and optimal -thresholding pursuit (OTP) are newly introduced frameworks of thresholding techniques for compressed sensing and signal approximat…

cs.IT2019

Optimal -thresholding algorithms for sparse optimization problems

Yun-Bin Zhao

The simulations indicate that the existing hard thresholding technique independent of the residual function may cause a dramatic increase or numerical oscillation of the residual.…

math.OC2019

Stability Analysis for a Class of Sparse Optimization Problems

Jialiang Xu, Yun-Bin Zhao

The sparse optimization problems arise in many areas of science and engineering, such as compressed sensing, image processing, statistical and machine learning. The -mini…