Archive for AgroParisTech

unbiased MCMC with couplings [4pm, 26 Feb., Paris]

Posted in Books, pictures, Statistics, University life with tags , , , , , , , , , , , on February 24, 2020 by xi'an

On Wednesday, 26 February, Pierre Jacob (Havard U, currently visiting Paris-Dauphine) is giving a seminar on unbiased MCMC methods with couplings at AgroParisTech, bvd Claude Bernard, Paris 5ième, Room 32, at 4pm in the All about that Bayes seminar.

MCMC methods yield estimators that converge to integrals of interest in the limit of the number of iterations. This iterative asymptotic justification is not ideal; first, it stands at odds with current trends in computing hardware, with increasingly parallel architectures; secondly, the choice of “burn-in” or “warm-up” is arduous. This talk will describe recently proposed estimators that are unbiased for the expectations of interest while having a finite computing cost and a finite variance. They can thus be generated independently in parallel and averaged over. The method also provides practical upper bounds on the distance (e.g. total variation) between the marginal distribution of the chain at a finite step and its invariant distribution. The key idea is to generate “faithful” couplings of Markov chains, whereby pairs of chains coalesce after a random number of iterations. This talk will provide an overview of this line of research.

Scott Sisson’s ABC seminar in Paris [All about that Bayes]

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , , on January 20, 2020 by xi'an

On the “All about that Bayes” seminar tomorrow (Tuesday 21 at 3p.m., room 42, AgroParisTech, 16 rue Claude Bernard, Paris 5ième), Scott Sisson, School of Mathematics and Statistics at UNSW, and visiting Paris-Dauphine this month, will give a talk on

Approximate posteriors and data for Bayesian inference

Abstract
For various reasons, including large datasets and complex models, approximate inference is becoming increasingly common. In this talk I will provide three vignettes of recent work. These cover a) approximate Bayesian computation for Gaussian process density estimation, b) likelihood-free Gibbs sampling, and c) MCMC for approximate (rounded) data.

tenured research position on ABC in Paris!

Posted in Statistics, University life with tags , , , , , , on February 2, 2013 by xi'an

Paris and la Seine, from Pont du Garigliano, Oct. 20, 2011Just to make sure this fabulous announcement has not gone undetected: there is a permanent research (I repeat, permanent research!) position in statistics is open at AgroParisTech/INRA (a French institute/school on biology, agronomy, veterinary sciences, environmental sciences) with the profile ‘Approximate inference methods for complex systems’ (Hence my title!). Applications must be received by February 28th. See here for more details on the profile and there for the application process. Please contact Eric PARENT for further information. (There are other tenured positions posted by INRA, and there will be a regular lecturer position at Paris-Dauphine opening soon.)