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Scale-Robust Timely Asynchronous Decentralized Learning
In this work, we investigate the staleness criteria for such a system, which is a sufficient condition for convergence of individual user models.
A Learning Based Scheme for Fair Timeliness in Sparse Gossip Networks
We consider a gossip network, consisting of $n$ nodes, which tracks the information at a source.
Timely Asynchronous Hierarchical Federated Learning: Age of Convergence
The goal of each client is to converge to the global model, while maintaining timeliness of the clients, i. e., having optimum training iteration time.
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