D-ADMM: A Communication-Efficient Distributed Algorithm for Separable Optimization

We propose a distributed algorithm, named Distributed Alternating Direction Method of Multipliers (D-ADMM), for solving separable optimization problems in networks of interconnected nodes or agents. In a separable optimization problem there is a private cost function and a private constraint set at...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on signal processing 2013-05, Vol.61 (10), p.2718-2723
Hauptverfasser:	Mota, J. F. C., Xavier, J. M. F., Aguiar, P. M. Q., Puschel, M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Algorithms Alternating direction method of multipliers Applied sciences Color Computer simulation Constraining Convergence Cost function Detection, estimation, filtering, equalization, prediction Distributed algorithms Exact sciences and technology Image color analysis Information, signal and communications theory Networks Optimization Sampling, quantization sensor networks Sensors Signal and communications theory Signal processing Signal representation. Spectral analysis Signal, noise Studies Telecommunications and information theory
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!