Guaranteed Upper Bounds for Iteration Errors and Modified Kačanov Schemes via Discrete Duality

Abstract We apply duality theory to discretized convex minimization problems to obtain computable guaranteed upper bounds for the distance of given discrete functions and the exact discrete minimizer. Furthermore, we show that the discrete duality framework extends convergence results for the Kačanov scheme to a broader class of problems.