Distributed Zero-Order Algorithms for Nonconvex Multiagent Optimization

Distributed multiagent optimization finds many applications in distributed learning, control, estimation, etc. Most existing algorithms assume knowledge of first-order information of the objective and have been analyzed for convex problems. However, there are situations where the objective is noncon...

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Veröffentlicht in:	IEEE transactions on control of network systems 2021-03, Vol.8 (1), p.269-281
Hauptverfasser:	Tang, Yujie, Zhang, Junshan, Li, Na
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Control systems Convergence Convex functions Distributed optimization Linear programming Machine learning Multiagent systems nonconvex optimization Optimization Radio frequency Two dimensional displays Zero order algorithms zero-order information
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