activity
20162019
most citedNonconvex fraction function recovery sparse signal by convex optimization algorithm

1 citations · 1 across the 3 of their papers we have counts for

collaborators

10 papers

math.OC20191 cited

Nonconvex fraction function recovery sparse signal by convex optimization algorithm

Angang Cui, Jigen Peng, Haiyang Li +1

In this paper, we will generate a convex iterative FP thresholding algorithm to solve the problem . Two schemes of convex iterative FP thresholding algorithms are gener…

math.OC2018

Iterative thresholding algorithm based on non-convex method for modified lp-norm regularization minimization

Angang Cui, Jigen Peng, Haiyang Li +2

Recently, the -norm regularization minimization problem has attracted great attention in compressed sensing. However, the -norm in problem…

math.OC2018

A New Nonconvex Strategy to Affine Matrix Rank Minimization Problem

Angang Cui, Jigen Peng, Haiyang Li +2

The affine matrix rank minimization (AMRM) problem is to find a matrix of minimum rank that satisfies a given linear system constraint. It has many applications in some important a…

math.OC2018

Sparse Portfolio Selection via Non-convex Fraction Function

Angang Cui, Jigen Peng, Chengyi Zhang +2

In this paper, a continuous and non-convex promoting sparsity fraction function is studied in two sparse portfolio selection models with and without short-selling constraints. Firs…

math.OC2017

Recovering Sparse Nonnegative Signals via Non-convex Fraction Function Penalty

Angang Cui, Haiyang Li, Meng Wen +1

Many real world practical problems can be formulated as -minimization problems with nonnegativity constraints, which seek the sparsest nonnegative signals to underdetermi…

math.OC2016

An inertial primal-dual fixed point algorithm for composite optimization problems

Meng Wen, Yu-Chao Tang, Jigen Peng

We consider an inertial primal-dual fixed point algorithm (IPDFP) to compute the minimizations of the following Problem (1.1). This is a full splitting approach, in the sense that…