Augmented Lagrangian methods for infeasible convex optimization problems and diverging proximal-point algorithms

Roland Andrews, Justin Carpentier, Adrien Taylor

This work investigates the convergence behavior of augmented Lagrangian methods (ALMs) when applied to convex optimization problems that may be infeasible. ALMs are a popular class…