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arxiv: 1704.06209 · v1 · pith:KMS4TX62new · submitted 2017-04-20 · 🧮 math.OC · cs.LG· eess.SP

ADMM Penalty Parameter Selection by Residual Balancing

classification 🧮 math.OC cs.LGeess.SP
keywords parameterselectionadmmheuristicmethodpenaltyaddressesalternating
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Appropriate selection of the penalty parameter is crucial to obtaining good performance from the Alternating Direction Method of Multipliers (ADMM). While analytic results for optimal selection of this parameter are very limited, there is a heuristic method that appears to be relatively successful in a number of different problems. The contribution of this paper is to demonstrate that their is a potentially serious flaw in this heuristic approach, and to propose a modification that at least partially addresses it.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. An Adaptive Multiparameter Penalty Selection Method for Multiconstraint and Multiblock ADMM

    eess.IV 2025-02 unverdicted novelty 6.0

    A new adaptive multiparameter penalty selection method for multiconstraint and multiblock ADMM provides robustness to scale differences and initial parameter choices.