Poster
Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling
Andrei-Cristian Barbos · Francois Caron · Jean-Fran├žois Giovannelli · Arnaud Doucet

Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #196 #None

We propose a generalized Gibbs sampler algorithm for obtaining samples approximately distributed from a high-dimensional Gaussian distribution. Similarly to Hogwild methods, our approach does not target the original Gaussian distribution of interest, but an approximation to it. Contrary to Hogwild methods, a single parameter allows us to trade bias for variance. We show empirically that our method is very flexible and performs well compared to Hogwild-type algorithms.

Author Information

Andrei-Cristian Barbos (University of Bordeaux)
Francois Caron (Oxford)
Jean-Fran├žois Giovannelli (University of Bordeaux)
Arnaud Doucet (Oxford)

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