1 citations · 2 across the 2 of their papers we have counts for
2 papers
math.OC2018★ 1 cited
A semi-proximal augmented Lagrangian based decomposition method for primal block angular convex composite quadratic conic programming problems
Xin-Yee Lam, Defeng Sun, Kim-Chuan Toh
We propose a semi-proximal augmented Lagrangian based decomposition method for convex composite quadratic conic programming problems with primal block angular structures. Using our…
math.OC2018★ 1 cited
Efficient sparse semismooth Newton methods for the clustered lasso problem
Meixia Lin, Yong-Jin Liu, Defeng Sun +1
We focus on solving the clustered lasso problem, which is a least squares problem with the -type penalties imposed on both the coefficients and their pairwise differences t…