A uniform momentum-based distributed stochastic gradient tracking algorithm for non-convex optimization

This paper investigates distributed non-convex optimization problems, specifically focusing on a collaborative approach to optimize a global non-convex objective function across agents over networks. Problems of this nature along with consideration of efficiency usually emerge in a number of applica...

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Veröffentlicht in:	Journal of the Franklin Institute Jg. 362; H. 15; S. 108040
Hauptverfasser:	Li, Yantao, Wu, Chaoxu, Chen, Yingjue, Zhang, Keke, Lü, Qingguo, Deng, Shaojiang, Li, Huaqing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.10.2025
Schlagworte:	Distributed optimization Gradient tracking Non-convex optimization Stochastic gradient Uniform momentum acceleration Uniform momentum acceleration Gradient tracking Distributed optimization Non-convex optimization Stochastic gradient
ISSN:	0016-0032
Online-Zugang:	Volltext
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