7 citations · 15 across the 13 of their papers we have counts for
4 papers · 1 filter
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…
A Dual Symmetric Gauss-Seidel Alternating Direction Method of Multipliers for Hyperspectral Sparse Unmixing
Longfei Ren, Chengjing Wang, Peipei Tang +1
Since sparse unmixing has emerged as a promising approach to hyperspectral unmixing, some spatial-contextual information in the hyperspectral images has been exploited to improve t…
A Dual Alternating Direction Method of Multipliers for Image Decomposition and Restoration
Qingsong Wang, Chengjing Wang, Peipei Tang +1
In this paper, we develop a dual alternating direction method of multipliers (ADMM) for an image decomposition model. In this model, an image is divided into two meaningful compone…