Asynchronous Gossip-Based Random Projection Algorithms for Fully Distributed Problems
نویسندگان
چکیده
We consider fully distributed constrained convex optimization problems over a network, where each network agent has a distinct objective and constraint set. We discuss a gossipbased random projection algorithm (GRP) with uncoordinated diminishing stepsizes. We prove that, when the problem has a solution, the iterates of all network agents converge to the same optimal point with probability 1.
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