Next Session - April 24 with Guanyang Wang

[All About That Bayes]

Dear all,

we will have a joint session with the Mostly Monte Carlo Seminar on April 24 at 16:00, room 8 at PariSanté Campus (2-10 Rue d’Oradour-sur-Glane, 75015 Paris). As usual the seminar will also be broadcasted online.

Guanyang Wang (Rutgers University) will give a talk on "MCMC when you do not want to evaluate the target distribution"

Best regards,

The All About that Bayes Team

Abstract: In sampling tasks, it is common for target distributions to be known up to a normalizing constant. However, in many situations, evaluating even the unnormalized distribution can be costly or infeasible. This issue arises in scenarios such as sampling from the Bayesian posterior for large datasets and the 'doubly intractable' distributions. We provide a way to unify various MCMC algorithms, including several minibatch MCMC algorithms and the exchange algorithm. This framework not only simplifies the theoretical analysis of existing algorithms but also creates new algorithms. Similar frameworks exist in the literature, but they concentrate on different objectives.