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Convergence Rate Comparison of Proximal Algorithms for Non-Smooth Convex Optimization With an Application to Texture Segmentation
In this paper we provide a theoretical and numerical comparison of convergence rates of forward-backward, Douglas-Rachford, and Peaceman-Rachford algorithms for minimizing the sum of a convex proper lower semicontinuous function and a strongly convex differentiable function with Lipschitz continuous gradient. Our results extend the comparison made in [1], when both …