Lapparadish

On top of BayesComp 2023 being rich and exciting, spending a week above the Arctic circle, by about 68⁰ North was most pleasurable. If we did not really see Northern Lights/auroras, as the above was taken by one of us with a long exposure shot on a particularly cold evening, rather than the diaphanous veils we could hardly perceive, cold and snow and associated activities were delivered without reservation!On the day we left, due to a late flight departure. we had an exhilarating 10k ride with three teams of Alaskan huskies, over a frozen river, following a musher. The strength of these dogs was amazing, esp. since they were not fully delivering, being able to reach 25km/hour in races over massive distances. On top, our guide delivered another and more realistic version of the story of Balto, whose musher was Finnish, and which we had watched many times with our kids (although we missed his statue in Central Park!)And I X country skied every early morning instead of running, over groomed trails and in all weathers, with a minimum (manageable) -24⁰ one morn. As a near neophyte in the game, I eventually developed a hip inflammation but the joy of going through the woods prior to sunrise and spotting the occasional Arctic hare was worth the 15 hours of it. Despite hard frozen glasses the coldest morns. By comparison, the afternoon break when I tried downhill skiing was less exciting even though the very dry snow there was enjoyable.Cold dry weather also re-awoke a nose bleed proclivity that I had forgotten since Arizona. Again, no big deal. And the conference dinner took place in a Sammi restaurant that proved quite the exception to my skip-the-conference-dinner rule with its reindeer and salmon dishes!

off to Bengaluru!

Elisabeth Gassiat, a path in modern statistics [conférence]

Next Spring (31 May-02 June 2023), there will be a conference at Institut de mathématique d’Orsay in honour of our friend Elisabeth Gassiat and her contributions to statistics over the past 35 years, with Emmanuel Candès (Stanford University), Alexandra Carpentier (Universität Potsdam), Fabrice Gamboa (Université Toulouse III-Paul Sabatier), Alice Guionnet (ENS Lyon), Ramon van Handel (Princeton University), Thi Thu Huong Hoang (EDF), Eric Moulines (École Polytechnique), Richard Nickl (University of Cambridge), Judith Rousseau (University of Oxford / Université Paris Dauphine – PSL), Adeline Samson (Université Grenoble Alpes), Jean-Christophe Thalabard (Université Paris Cité), and Aad van der Vaart (TU Delft) as invited speakers. Registration is free and compulsory!

BNP13

BNP13 is set in this incredible location on a massive lake (almost as large as Lac Saint Jean!) facing several tantalizing snow-capped volcanoes… My trip from Paris to Puerto Varas was quite smooth if relatively longish (but I slept close to 8 hours on the first leg and busied myself with Biometrika submissions the rest of the way). Leaving from Paris at midnight proved a double advantage as this was one of the last flights leaving, with hardly anyone in the airport. On Sunday, I arrived early enough to take a quick dip in Lake Llanquihue which was fairly cold and choppy!

Overall the conference is quite exhilarating as all talks are of interest and often covering on-going research. This may be one of the most engaging meetings I have attended in the past years! Plus a refreshing variety of topics and seniority in the speakers.

To start with a bang!, Sonia Petrone (Bocconi) gave a very nice plenary lecture in the most auspicious manner, covering her recent works on Bayesian prediction as an alternative way to run Bayesian inference (in connection with the incoming Read Paper by Fong et al.). She covered so much ground that I got lost before long (jetlag did not help!). However, an interesting feature underlying her talk is that, under exchangeability, the sequence of predictives converges to a random probability measure, a de Finetti way to construct the prior that is based on predictives. Avoiding in a sense the model and the prior on the parameters of that process. (The parameter is derived from the infinite exchangeable [or conditionally iid] sequence, but the sequence of predictives need be defined.) The drawback is that this approach involves infinite sequences, with practical truncation to a finite horizon being an approximation whose precision / error may prove elusive to characterise. The predictive approach also allows to recover a limiting Normal distribution (not a Bernstein-von Mises type!) and hence credible intervals on parameters and distributions.

While this is indeed a BNP conference (!), I was surprised to see lot of talks paying attention to clustering and even to mixtures, with again a recurrent imprecision on the meaning of a cluster. (Maybe this was already the case for BNP11 in Paris but I may have been too busy helping with catering to notice!) For instance, Brian Trippe (MIT) gave a quick intro on his (AISTATS 2022) work on parallel MCMC with coupling. As unbiased MCMC strongly improving upon naïve parallel MCMC relative to the computing cost. With an interesting example where coupling is agnostic to the labeling of random partitions in clustering problems, involving optimal transport, manageable in O(K³log(K)) time when K is the number of clusters.

sunrise on Lago Llanquihue [jatp]