Distributed stochastic gradient tracking methods

In this paper, we study the problem of distributed multi-agent optimization over a network, where each agent possesses a local cost function that is smooth and strongly convex. The global objective is to find a common solution that minimizes the average of all cost functions. Assuming agents only ha...

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Veröffentlicht in:	Mathematical programming Jg. 187; H. 1-2; S. 409 - 457
Hauptverfasser:	Pu, Shi, Nedić, Angelia
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2021 Springer Nature B.V
Schlagworte:	Algorithms Calculus of Variations and Optimal Control; Optimization Combinatorics Computing costs Cost function Full Length Paper Mathematical and Computational Physics Mathematical Methods in Physics Mathematics Mathematics and Statistics Mathematics of Computing Multiagent systems Numerical Analysis Optimization Theoretical Tracking 68Q25 Distributed optimization 90C25 90C15 Stochastic optimization Communication networks Convex programming
ISSN:	0025-5610, 1436-4646
Online-Zugang:	Volltext
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