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• W3136014883 abstract "In this paper, we consider a prototypical convex optimization problem with multi-block variables and separable structures. By adding the Logarithmic Quadratic Proximal (LQP) regularizer with suitable proximal parameter to each of the first grouped subproblems, we develop a partial LQP-based Alternating Direction Method of Multipliers (ADMM-LQP). The dual variable is updated twice with relatively larger stepsizes than the classical region (0,1+52). Using a prediction-correction approach to analyze properties of the iterates generated by ADMM-LQP, we establish its global convergence and sublinear convergence rate of O(1/T) in the new ergodic and nonergodic senses, where T denotes the iteration index. We also extend the algorithm to a nonsmooth composite convex optimization and establish similar convergence results as our ADMM-LQP." @default.
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• W3136014883 date "2021-07-01" @default.
• W3136014883 modified "2023-09-27" @default.
• W3136014883 title "Iteration complexity analysis of a partial LQP-based alternating direction method of multipliers" @default.
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• W3136014883 doi "https://doi.org/10.1016/j.apnum.2021.03.014" @default.
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