Distributed Algorithms for Composite Optimization: Unified Framework and Convergence Analysis

We study distributed composite optimization over networks: agents minimize a sum of smooth (strongly) convex functions-the agents' sum-utility-plus a nonsmooth (extended-valued) convex one. We propose a general unified algorithmic framework for such a class of problems and provide a convergence...

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Veröffentlicht in:	IEEE transactions on signal processing Jg. 69; S. 3555 - 3570
Hauptverfasser:	Xu, Jinming, Tian, Ye, Sun, Ying, Scutari, Gesualdo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Convergence Decoupling Distributed algorithms Distributed optimization Electronic mail Heterogeneity linear convergence Network topologies Network topology Operators (mathematics) Optimization Signal processing algorithms Sun Tuning
ISSN:	1053-587X, 1941-0476
Online-Zugang:	Volltext
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