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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…
math.OC2021
Indefinite linearized augmented Lagrangian method for convex programming with linear inequality constraints
Bingsheng He, Shengjie Xu, Jing Yuan
The augmented Lagrangian method (ALM) is a benchmark for convex programming problems with linear constraints; ALM and its variants for linearly equality-constrained convex minimiza…