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In this paper, we propose a decentralized distributed algorithm with stochastic communication among nodes, building on a sampling method called "edge ...
In this paper, we propose a decentralized dis- tributed algorithm with stochastic communication among nodes, building on a sampling method called “edge ...
In this paper, we propose a decentralized distributed algorithm with stochastic communication among nodes, building on a sampling method called "edge ...
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Any optimization method can be executed over the network through relayed communication over multiple edges. ... They utilize W, while U is used only in analysis.
Missing: Sampling. | Show results with:Sampling.
Jan 24, 2024 · Abstract—Consensus-based decentralized stochastic gradient descent (D-SGD) is a widely adopted algorithm for decentralized.
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Apr 13, 2024 · Efficient decentralized optimization for edge-enabled smart manufacturing: A federated learning-based framework ; Huan Liu ; Shiyong Li ; Wenzhe Li.
Abstract—We consider decentralized optimization problems in which a number of agents collaborate to minimize the average of.
In the setting where a constant number of edges changes at each iteration, our results allow to establish the known lower bounds for static graphs and time- ...
Abstract. One fundamental problem in decentralized multi-agent optimization is the trade-off. 5 between gradient/sampling complexity and communication ...