Double Averaging and Gradient Projection: Convergence Guarantees for Decentralized Constrained Optimization

We consider a generic decentralized constrained optimization problem over static, directed communication networks, where each agent has exclusive access to only one convex, differentiable, local objective term and one convex constraint set. For this setup, we propose a novel decentralized algorithm,...

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Vydáno v:	IEEE transactions on automatic control Ročník 70; číslo 5; s. 3433 - 3440
Hlavní autoři:	Shahriari-Mehr, Firooz, Panahi, Ashkan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.05.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Communication networks Computer architecture Computer Sciences Constrained optimization Constraints Convergence convergence analysis Convex functions convex optimization Convexity Datavetenskap (datalogi) Directed graphs distributed optimization Liapunov functions Linear programming Lyapunov methods Networked, Parallel and Distributed Computing Nätverks-, parallell- och distribuerad beräkning Optimization Optimization methods Smoothness Vectors
ISSN:	0018-9286, 1558-2523, 1558-2523
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