Preconditioned ADMM with Nonlinear Operator Constraint

Abstract : We are presenting a modification of the well-known Alternating Direction Method of Multipliers (ADMM) algorithm with additional preconditioning that aims at solving convex optimisation problems with nonlinear operator constraints. Connections to the recently developed Nonlinear Primal-Dual Hybrid Gradient Method (NL-PDHGM) are presented, and the algorithm is demonstrated to handle the nonlinear inverse problem of parallel Magnetic Resonance Imaging (MRI).
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Communication dans un congrès
Lorena Bociu; Jean-Antoine Désidéri; Abderrahmane Habbal. 27th IFIP Conference on System Modeling and Optimization (CSMO), Jun 2015, Sophia Antipolis, France. Springer International Publishing, IFIP Advances in Information and Communication Technology, AICT-494, pp.117-126, 2016, System Modeling and Optimization. 〈10.1007/978-3-319-55795-3_10〉
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Soumis le : mardi 31 octobre 2017 - 14:40:04
Dernière modification le : lundi 15 janvier 2018 - 11:43:26

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Florian Knoll, Carola-Bibiane Schönlieb, Tuomo Valkonen, Martin Benning. Preconditioned ADMM with Nonlinear Operator Constraint. Lorena Bociu; Jean-Antoine Désidéri; Abderrahmane Habbal. 27th IFIP Conference on System Modeling and Optimization (CSMO), Jun 2015, Sophia Antipolis, France. Springer International Publishing, IFIP Advances in Information and Communication Technology, AICT-494, pp.117-126, 2016, System Modeling and Optimization. 〈10.1007/978-3-319-55795-3_10〉. 〈hal-01626884〉

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