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cs.LG2021
A General Theory for Client Sampling in Federated Learning
Yann Fraboni, Richard Vidal, Laetitia Kameni +1
While client sampling is a central operation of current state-of-the-art federated learning (FL) approaches, the impact of this procedure on the convergence and speed of FL remains…
cs.LG2021★ 47 cited
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Yann Fraboni, Richard Vidal, Laetitia Kameni +1
This work addresses the problem of optimizing communications between server and clients in federated learning (FL). Current sampling approaches in FL are either biased, or non opti…