EXPLICIT AND EFFICIENT ERROR ESTIMATION FOR CONVEX MINIMIZATION PROBLEMS

We combine a systematic approach for deriving general a posteri-ori error estimates for convex minimization problems based on convex duality relations with a recently derived generalized Marini formula. The a posteriori error estimates are quasi constant-free and apply to a large class of variational problems including the p-Dirichlet problem, as well as degenerate minimiza-tion, obstacle and image de-noising problems. In addition, these a posteriori error estimates are based on a comparison to a given non-conforming finite element solution. For the p-Dirichlet problem, these a posteriori error bounds are equivalent to residual type a posteriori error bounds and, hence, reliable and efficient.