488 citations · 3k across the 119 of their papers we have counts for
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cs.LG2021★ 3 cited
QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning
Maxime Vono, Vincent Plassier, Alain Durmus +2
The objective of Federated Learning (FL) is to perform statistical inference for data which are decentralised and stored locally on networked clients. FL raises many constraints wh…
cs.LG2021
The Perturbed Prox-Preconditioned SPIDER algorithm for EM-based large scale learning
Gersende Fort, Eric Moulines
Incremental Expectation Maximization (EM) algorithms were introduced to design EM for the large scale learning framework by avoiding the full data set to be processed at each itera…