Convergence analysis of an inexact relaxed augmented Lagrangian method

In this paper, we develop an Inexact Relaxed Augmented Lagrangian Method (IR-ALM) for solving a class of convex optimization problems. Flexible relative error criteria are designed for approximately solving the resulting subproblem, and a relaxation step is exploited to accelerate its convergence numerically. By a unified variational analysis, we establish the global convergence of this … Read more

ADMM and inexact ALM: the QP case

Embedding randomization procedures in the Alternating Direction Method of Multipliers (ADMM) has recently attracted an increasing amount of interest as a remedy to the fact that the direct n-block generalization of ADMM is not necessarily convergent ($n \geq 3$). Even if, in practice, the introduction of such techniques could mitigate the diverging behaviour of the … Read more