2 citations · 2 across the 1 of their papers we have counts for
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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…
Asymptotically exact data augmentation: models, properties and algorithms
Maxime Vono, Nicolas Dobigeon, Pierre Chainais
Data augmentation, by the introduction of auxiliary variables, has become an ubiquitous technique to improve convergence properties, simplify the implementation or reduce the compu…
Split-and-augmented Gibbs sampler - Application to large-scale inference problems
Maxime Vono, Nicolas Dobigeon, Pierre Chainais
This paper derives two new optimization-driven Monte Carlo algorithms inspired from variable splitting and data augmentation. In particular, the formulation of one of the proposed…