Preconditioned ADMM with nonlinear operator constraint

Benning M, Knoll F, Schönlieb CB, Valkonen T (2016)

Publication Type: Conference contribution

Publication year: 2016

Journal

IFIP Advances in Information and Communication Technology Springer Verlag

Publisher: Springer New York LLC

Book Volume: 494

Pages Range: 117-126

Conference Proceedings Title: IFIP Advances in Information and Communication Technology

Event location: Sophia Antipolis, FRA

ISBN: 9783319557946

DOI: 10.1007/978-3-319-55795-3_10

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).

Authors with CRIS profile

Florian Knoll

Involved external institutions

University of Cambridge GB United Kingdom (GB) The University of Liverpool GB United Kingdom (GB) New York University (NYU) US United States (USA) (US)

How to cite

APA:

Benning, M., Knoll, F., Schönlieb, C.B., & Valkonen, T. (2016). Preconditioned ADMM with nonlinear operator constraint. In Jean-Antoine Desideri, Abderrahmane Habbal, Lorena Bociu (Eds.), IFIP Advances in Information and Communication Technology (pp. 117-126). Sophia Antipolis, FRA: Springer New York LLC.

MLA:

Benning, Martin, et al. "Preconditioned ADMM with nonlinear operator constraint." Proceedings of the 27th IFIP TC7 Conference on System Modeling and Optimization, CSMO 2015, Sophia Antipolis, FRA Ed. Jean-Antoine Desideri, Abderrahmane Habbal, Lorena Bociu, Springer New York LLC, 2016. 117-126.

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