Feng-Yi Liao

Inexact Augmented Lagrangian Methods for Conic Optimization: Quadratic Growth and Linear Convergence

Augmented Lagrangian Methods (ALMs) are widely employed in solving constrained optimizations, and some efficient solvers are developed based on this framework. Under the quadratic growth assumption, it is known that the dual iterates and the Karush–Kuhn–Tucker (KKT) residuals of ALMs applied to coni…