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20212025
most citedQLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning

3 citations · 9 across the 8 of their papers we have counts for

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stat.ME2021★ 2 cited

DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs

Vincent Plassier, Maxime Vono, Alain Durmus +1

Performing reliable Bayesian inference on a big data scale is becoming a keystone in the modern era of machine learning. A workhorse class of methods to achieve this task are Marko…

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…