Convergence analysis of the relaxed proximal point algorithm (Q2319250)

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Convergence analysis of the relaxed proximal point algorithm
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    Convergence analysis of the relaxed proximal point algorithm (English)
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    16 August 2019
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    Summary: Recently, a worst-case \(O(1 / t)\) convergence rate was established for the Douglas-Rachford alternating direction method of multipliers (ADMM) in an ergodic sense. The relaxed proximal point algorithm (PPA) is a generalization of the original PPA which includes the Douglas-Rachford ADMM as a special case. In this paper, we provide a simple proof for the same convergence rate of the relaxed PPA in both ergodic and nonergodic senses.
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