3 citations · 5 across the 3 of their papers we have counts for
3 papers
math.OC2022★ 2 cited
On construction of splitting contraction algorithms in a prediction-correction framework for separable convex optimization
Bingsheng He, Xiaoming Yuan
In the past decade, we had developed a series of splitting contraction algorithms for separable convex optimization problems, at the root of the alternating direction method of mul…
math.OC2021★ 3 cited
Balanced Augmented Lagrangian Method for Convex Programming
Bingsheng He, Xiaoming Yuan
We consider the convex minimization model with both linear equality and inequality constraints, and reshape the classic augmented Lagrangian method (ALM) by balancing its subproble…
math.OC2021
Extensions of ADMM for Separable Convex Optimization Problems with Linear Equality or Inequality Constraints
Bingsheng He, Shengjie Xu, Xiaoming Yuan
The alternating direction method of multipliers (ADMM) proposed by Glowinski and Marrocco is a benchmark algorithm for two-block separable convex optimization problems with linear…