This morning I attended the “Bruce Schmeiser session” at WSC 2011. I had once a meeting with Bruce (and Jim Berger) in Purdue to talk about MCMC methods but I never interacted directly with him. The first two talks were about batch methods, which I did not know previously, and I had trouble understanding what was the problem: for a truly iid normal sample, building an optimal confidence interval on the mean relies on the sufficient statistic rather than on the batch mean variance… It is only through the second talk that I understood that neither normality nor independence was guaranteed, hence the batches. I still wonder whether or a bootstrap strategy could be used instead, given the lack of confidence in the model assumptions. The third talk was about a stochastic approximation algorithm developed by Bruce Schmeiser, called retrospective approximation, where successive and improving approximations of the target to maximise are used in order not to waste time at the beginning. I thus found the algorithm had a simulated annealing flavour, even though the connection is rather tenuous…
The second session of WSC 2011 I attended was about importance sampling, The first talk was about mixtures of importance sampling distributions towards improved efficiency for cross-entropy, à la Rubinstein and Kroese. Its implementation seemed to depend very much on some inner knowledge of the target problem. The second talk was on zero-variance approximations for computing the probability that two notes are connected in a graph, using clever collapsing schemes. The third talk of the session was unrelated with the theme since it was about cross-validated non-parametric density estimation.
My own session was not terribly well attended and, judging from some questions I got at the end I am still unsure I had chosen the right level. Nonetheless, I got interesting discussions afterwards which showed that ABC was also appealing to some members of the audience. And I had a long chat with Enlu Zhou, a nice assistant professor from Urbana-Champaign who was teaching out of Monte Carlo Statistical Method, and had challenging questions about restricted support MCMC. Overall, an interesting day, completed with a light conference dinner in the pleasant company of Jingchen Liu from Columbia and some friends of his.
