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Achieving Linear Convergence in Distributed Asynchronous Multi-agent Optimization
[article]
2019
arXiv
pre-print
This papers studies multi-agent (convex and nonconvex) optimization over static digraphs. We propose a general distributed asynchronous algorithmic framework whereby i) agents can update their local variables as well as communicate with their neighbors at any time, without any form of coordination; and ii) they can perform their local computations using (possibly) delayed, out-of-sync information from the other agents. Delays need not be known to the agent or obey any specific profile, and can
arXiv:1803.10359v4
fatcat:qdeplzkdxfbddgzkuwlkhky7l4