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• W4313656994 endingPage "127801" @default.
• W4313656994 startingPage "127801" @default.
• W4313656994 abstract "In this paper, we study a class of distributed constraint-coupled optimization problems, where each local function is composed of a smooth and strongly convex function and a convex but possibly non-smooth function. We design a novel proximal nested primal-dual gradient algorithm (Prox-NPGA), which is a generalized version of the exiting algorithm–NPGA. The convergence of Prox-NPGA is proved and the upper bounds of the step-sizes are given. Finally, numerical experiments are employed to verify the theoretical results and compare the convergence rates of different versions of Prox-NPGA." @default.
• W4313656994 created "2023-01-07" @default.
• W4313656994 creator A5001673064 @default.
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• W4313656994 date "2023-05-01" @default.
• W4313656994 modified "2023-10-16" @default.
• W4313656994 title "Proximal nested primal-dual gradient algorithms for distributed constraint-coupled composite optimization" @default.
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• W4313656994 doi "https://doi.org/10.1016/j.amc.2022.127801" @default.
• W4313656994 hasPublicationYear "2023" @default.
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