58 citations · 75 across the 15 of their papers we have counts for
15 papers
Adaptive Algorithm for Quantum Amplitude Estimation
Yunpeng Zhao, Haiyan Wang, Kuai Xu +3
Quantum amplitude estimation is a key sub-routine of a number of quantum algorithms with various applications. We propose an adaptive algorithm for interval estimation of amplitude…
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…
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…
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…
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…
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.…
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…
A Theoretical Analysis of Sparse Recovery Stability of Dantzig Selector and LASSO
Yun-Bin Zhao, Duan Li
Dantzig selector (DS) and LASSO problems have attracted plenty of attention in statistical learning, sparse data recovery and mathematical optimization. In this paper, we provide a…
Weak Stability of -minimization Methods in Sparse Data Reconstruction
Yun-Bin Zhao, Houyuan Jiang, Zhi-Quan Luo
As one of the most plausible convex optimization methods for sparse data reconstruction, -minimization plays a fundamental role in the development of sparse optimization th…
1-Bit Compressive Sensing: Reformulation and RRSP-Based Sign Recovery Theory
Yun-Bin Zhao, Chunlei XU
Recently, the 1-bit compressive sensing (1-bit CS) has been studied in the field of sparse signal recovery. Since the amplitude information of sparse signals in 1-bit CS is not ava…
Uniqueness Conditions for A Class of l0-Minimization Problems
Chunlei Xu, Yun-Bin Zhao
We consider a class of l0-minimization problems, which is to search for the partial sparsest solution to an underdetermined linear system with additional constraints. We introduce…
New and Improved Conditions for Uniqueness of Sparsest Solutions of Underdetermined Linear Systems
Yun-Bin Zhao
The uniqueness of sparsest solutions of underdetermined linear systems plays a fundamental role in the newly developed compressed sensing theory. Several new algebraic concepts, in…
Rank-one Solutions for Homogeneous Linear Matrix Equations over the Positive Semidefinite Cone
Yunbin Zhao, Masao Fukushima
The problem of finding a rank-one solution to a system of linear matrix equations arises from many practical applications. Given a system of linear matrix equations, however, such…
Approximation Theory of Matrix Rank Minimization and Its Application to Quadratic Equations
Yun-Bin Zhao
Matrix rank minimization problems are gaining a plenty of recent attention in both mathematical and engineering fields. This class of problems, arising in various and across-discip…
Convexity Conditions of Kantorovich Function and Related Semi-infinite Linear Matrix Inequalities
Yun-Bin Zhao
The Kantorovich function , where is a positive definite matrix, is not convex in general. From matrix/convex analysis point of view, it is interesting to…