Double-proximal augmented Lagrangian methods with improved convergence condition
In this paper, we consider a family of linearly constrained convex minimization problems whose objective function is not necessarily smooth. A preliminary double-proximal augmented Lagrangian method (DP-ALM) is developed, which enjoys a flexible dual stepsize and a proximal subproblem with relatively smaller proximal parameter. By a novel prediction-correction reformulation for the proposed DP-ALM and by … Read more