València 9 snapshot [2]

During the poster session of Thursday night, between talking with old friends and keeping my bedtime in sight, I only had the opportunity to see less than one fourth of the posters! This is unfortunate as there were [too] many good things there. In particular, I talked with Mark Girolami about his Hamiltonian version of the MCMC algorithm. (This paper is most likely going to be a discussion paper at the Royal Statistical Society, so I will discuss it later!) I also saw a poster on ABC using a pseudo-likelihood to resort to the pseudo-MLE as a summary statistic. Leaving early allowed me to go running in Friday morning and enjoy a beautiful sunrise.

The computational session of Friday morning was (of course!) quite interesting and I discovered the TPA algorithm of Mark Huber that somehow looks like an “exact” nested sampling. (Is this getting into a Valencia tradition?!) The convergence results were surprising but, as Gareth Roberts pointed out, the applicability of the method is limited to cases where slice sampling also applies… Hedie Lopes gave a very enjoyable rendering of his particle learning paper, acknowledging more clearly the dependence of the convergence speed on the number of observations. Nick Polson gave a talk about sparsity and Lasso that related with James-Stein estimators, bringing back memories of my early research, but I am not convinced that minimaxity imperatives and sparsity requirements are that compatible… One of the last talks of the day was by Chris Holmes about harnessing the immense power of graphic cards or even playstations into parallel processing and this was a wonderful prospect, even though the programming that it involves is not innocuous. (This also reminded me of Peter Green’s feat in using the power of laser-printers at a [not-that-remote] time they were the most powerful machine in his department!)