2 citations · 2 across the 3 of their papers we have counts for
5 papers
An efficient algorithm for the norm based metric nearness problem
Peipei Tang, Bo Jiang, Chengjing Wang
Given a dissimilarity matrix, the metric nearness problem is to find the nearest matrix of distances that satisfy the triangle inequalities. This problem has wide applications, suc…
A proximal-proximal majorization-minimization algorithm for nonconvex tuning-free robust regression problems
Peipei Tang, Chengjing Wang, Bo Jiang
In this paper, we introduce a proximal-proximal majorization-minimization (PPMM) algorithm for nonconvex tuning-free robust regression problems. The basic idea is to apply the prox…
Estimation of sparse Gaussian graphical models with hidden clustering structure
Meixia Lin, Defeng Sun, Kim-Chuan Toh +1
Estimation of Gaussian graphical models is important in natural science when modeling the statistical relationships between variables in the form of a graph. The sparsity and clust…
A sparse semismooth Newton based augmented Lagrangian method for large-scale support vector machines
Dunbiao Niu, Chengjing Wang, Peipei Tang +2
Support vector machines (SVMs) are successful modeling and prediction tools with a variety of applications. Previous work has demonstrated the superiority of the SVMs in dealing wi…
A sparse semismooth Newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problems
Peipei Tang, Chengjing Wang, Defeng Sun +1
In this paper, we consider high-dimensional nonconvex square-root-loss regression problems and introduce a proximal majorization-minimization (PMM) algorithm for these problems. Ou…