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

Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #196
in Posters Mon »

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.

Keywords: MCMC
[ Paper] 

Author Information

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

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