Web: http://arxiv.org/abs/2207.07543

Sept. 16, 2022, 1:12 a.m. | Marina Costantini, Nikolaos Liakopoulos, Panayotis Mertikopoulos, Thrasyvoulos Spyropoulos

cs.LG updates on arXiv.org arxiv.org

In decentralized optimization environments, each agent $i$ in a network of
$n$ nodes has its own private function $f_i$, and nodes communicate with their
neighbors to cooperatively minimize the aggregate objective $\sum_{i=1}^n f_i$.
In this setting, synchronizing the nodes' updates incurs significant
communication overhead and computational costs, so much of the recent
literature has focused on the analysis and design of asynchronous optimization
algorithms, where agents activate and communicate at arbitrary times without
needing a global synchronization enforcer. However, most …

arxiv asynchronous decentralized math optimization

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