Abstract
We consider a dual method for solving non-strictly convex programs possessing a certain separable structure. This method may be viewed as a dual version of a block coordinate ascent method studied by Auslender [1, Section 6]. We show that the decomposition methods of Han [6, 7] and the method of multipliers may be viewed as special cases of this method. We also prove a convergence result for this method which can be applied to sharpen the available convergence results for Han's methods.
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The main part of this research was conducted while the author was with the Laboratory for Information and Decision Systems, M.I.T., Cambridge, with support by the U.S. Army Research Office, Contract No. DAAL03-86-K-0171 (Center for Intelligent Control Systems) and by the National Science Foundation under Grant ECS-8519058.
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Tseng, P. Dual coordinate ascent methods for non-strictly convex minimization. Mathematical Programming 59, 231–247 (1993). https://doi.org/10.1007/BF01581245
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DOI: https://doi.org/10.1007/BF01581245