Archive for Valencia meeting

O’Bayes 19/1 [snapshots]

Posted in Books, pictures, Statistics, University life with tags , , , , , , , , , , , , , , , , , on June 30, 2019 by xi'an

Although the tutorials of O’Bayes 2019 of yesterday were poorly attended, albeit them being great entries into objective Bayesian model choice, recent advances in MCMC methodology, and the multiple layers of BART, for which I have to blame myself for sticking the beginning of O’Bayes too closely to the end of BNP as only the most dedicated could achieve the commuting from Oxford to Coventry to reach Warwick in time, the first day of talks were well attended, despite weekend commitments, conference fatigue, and perfect summer weather! Here are some snapshots from my bench (and apologies for not covering better the more theoretical talks I had trouble to follow, due to an early and intense morning swimming lesson! Like Steve Walker’s utility based derivation of priors that generalise maximum entropy priors. But being entirely independent from the model does not sound to me like such a desirable feature… And Natalia Bochkina’s Bernstein-von Mises theorem for a location scale semi-parametric model, including a clever construct of a mixture of two Dirichlet priors to achieve proper convergence.)

Jim Berger started the day with a talk on imprecise probabilities, involving the society for imprecise probability, which I discovered while reading Keynes’ book, with a neat resolution of the Jeffreys-Lindley paradox, when re-expressing the null as an imprecise null, with the posterior of the null no longer converging to one, with a limit depending on the prior modelling, if involving a prior on the bias as well, with Chris discussing the talk and mentioning a recent work with Edwin Fong on reinterpreting marginal likelihood as exhaustive X validation, summing over all possible subsets of the data [using log marginal predictive].Håvard Rue did a follow-up talk from his Valencià O’Bayes 2015 talk on PC-priors. With a pretty hilarious introduction on his difficulties with constructing priors and counseling students about their Bayesian modelling. With a list of principles and desiderata to define a reference prior. However, I somewhat disagree with his argument that the Kullback-Leibler distance from the simpler (base) model cannot be scaled, as it is essentially a log-likelihood. And it feels like multivariate parameters need some sort of separability to define distance(s) to the base model since the distance somewhat summarises the whole departure from the simpler model. (Håvard also joined my achievement of putting an ostrich in a slide!) In his discussion, Robin Ryder made a very pragmatic recap on the difficulties with constructing priors. And pointing out a natural link with ABC (which brings us back to Don Rubin’s motivation for introducing the algorithm as a formal thought experiment).

Sara Wade gave the final talk on the day about her work on Bayesian cluster analysis. Which discussion in Bayesian Analysis I alas missed. Cluster estimation, as mentioned frequently on this blog, is a rather frustrating challenge despite the simple formulation of the problem. (And I will not mention Larry’s tequila analogy!) The current approach is based on loss functions directly addressing the clustering aspect, integrating out the parameters. Which produces the interesting notion of neighbourhoods of partitions and hence credible balls in the space of partitions. It still remains unclear to me that cluster estimation is at all achievable, since the partition space explodes with the sample size and hence makes the most probable cluster more and more unlikely in that space. Somewhat paradoxically, the paper concludes that estimating the cluster produces a more reliable estimator on the number of clusters than looking at the marginal distribution on this number. In her discussion, Clara Grazian also pointed the ambivalent use of clustering, where the intended meaning somehow diverges from the meaning induced by the mixture model.

O-Bayes15 [day #1]

Posted in Books, pictures, Running, Statistics, Travel, University life, Wines with tags , , , , , , on June 3, 2015 by xi'an

vale3So here we are back together to talk about objective Bayes methods, and in the City of Valencià as well.! A move back to a city where the 1998 O’Bayes took place. In contrast with my introductory tutorial, the morning tutorials by Luis Pericchi and Judith Rousseau were investigating fairly technical and advanced, Judith looking at the tools used in the frequentist (Bernstein-von Mises) analysis of priors, with forays in empirical Bayes, giving insights into a wide range of recent papers in the field. And Luis covering works on Bayesian robustness in the sense of resisting to over-influential observations. Following works of him and of Tony O’Hagan and coauthors. Which means characterising tails of prior versus sampling distribution to allow for the posterior reverting to the prior in case of over-influential datapoints. Funny enough, after a great opening by Carmen and Ed remembering Susie, Chris Holmes also covered Bayesian robust analysis. More in the sense of incompletely or mis-  specified models. (On the side, rekindling one comment by Susie and the need to embed robust Bayesian analysis within decision theory.) Which was also much Chris’ point, in line with the recent Watson and Holmes’ paper. Dan Simpson in his usual kick-the-anthill-real-hard-and-set-fire-to-it discussion pointed out the possible discrepancy between objective and robust Bayesian analysis. (With lines like “modern statistics has proven disruptive to objective Bayes”.) Which is not that obvious because the robust approach simply reincorporates the decision theory within the objective framework. (Dan also concluded with the comic strip below, whose message can be interpreted in many ways…! Or not.)

The second talk of the afternoon was given by Veronika Ročková on a novel type of spike-and-slab prior to handle sparse regression, bringing an alternative to the standard Lasso. The prior is a mixture of two Laplace priors whose scales are constrained in connection with the actual number of non-zero coefficients. I had not heard of this approach before (although Veronika and Ed have an earlier paper on a spike-and-slab prior to handle multicolinearity that Veronika presented in Boston last year) and I was quite impressed by the combination of minimax properties and practical determination of the scales. As well as by the performances of this spike-and-slab Lasso. I am looking forward the incoming paper!

The day ended most nicely in the botanical gardens of the University of Valencià, with an outdoor reception surrounded by palm trees and parakeet cries…

ISBA 2016 [logo]

Posted in pictures, Statistics, Travel, University life, Wines with tags , , , , , , , , , , on April 22, 2015 by xi'an

Things are starting to get in place for the next ISBA 2016 World meeting, in Forte Village Resort Convention Center, Sardinia, Italy. June 13-17, 2016. And not only the logo inspired from the nuraghe below. I am sure the program will be terrific and make this new occurrence of a “Valencia meeting” worth attending. Just like the previous occurrences, e.g. Cancún last summer and Kyoto in 2012.

However, and not for the first time, I wonder at the sustainability of such meetings when faced with always increasing—or more accurately sky-rocketing!—registration fees… We have now reached €500 per participant for the sole (early reg.) fees, excluding lodging, food or transportation. If we bet on 500 participants, this means simply renting the convention centre would cost €250,000 for the four or five days of the meeting. This sounds enormous, even accounting for the processing costs of the congress organiser. (By comparison, renting the convention centre MCMSki in Chamonix for three days was less than €20,000.) Given the likely high costs of staying at the resort, it is very unlikely I will be able to support my PhD students  As I know very well of the difficulty to find dedicated volunteers willing to offer a large fraction of their time towards the success of behemoth meetings, this comment is by no means aimed at my friends from Cagliari who kindly accepted to organise this meeting. But rather at the general state of academic meetings which costs makes them out of reach for a large part of the scientific community.

Thus, this makes me wonder anew whether we should move to a novel conference model given that the fantastic growth of the Bayesian community makes the ideal of gathering together in a single beach hotel for a week of discussions, talks, posters, and more discussions unattainable. If truly physical meetings are to perdure—and this notion is as debatable as the one about the survival of paper versions of the journals—, a new approach would be to find a few universities or sponsors able to provide one or several amphitheatres around the World and to connect all those places by teleconference. Reducing the audience size at each location would greatly the pressure to find a few huge and pricey convention centres, while dispersing the units all around would diminish travel costs as well. There could be more parallel sessions and ways could be found to share virtual poster sessions, e.g. by having avatars presenting some else’s poster. Time could be reserved for local discussions of presented papers, to be summarised later to the other locations. And so on… Obviously, something would be lost of the old camaraderie, sharing research questions and side stories, as well as gossips and wine, with friends from all over the World. And discovering new parts of the World. But the cost of meetings is already preventing some of those friends to show up. I thus think it is time we reinvent the Valencia meetings into the next generation. And move to the Valenci-e-meetings.

València 9 snapshot [2]

Posted in pictures, Statistics, Travel, University life with tags , , , , , on June 6, 2010 by xi'an

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!)

València 9 snapshot [1]

Posted in Mountains, Running, Statistics, Travel, University life with tags , , , , , on June 5, 2010 by xi'an

Last morning, I attended the talks of Michael Goldstein and Herbie Lee, which were very interesting from very different perspectives. Michael talked about computer models, like the climate models that have been so much attacked recently for being “unrealistic”. The difficulty is obviously in dealing with the fact that the model is incorrect, what Michael calls external uncertainty. As statisticians, we are trained to deal with internal uncertainties, i.e. those conditional on the model. Michael did not propose a generic solution to this difficult problem, but he presented a series of principles towards this goal and his paper in the proceeedings (I have not [yet] read) contains examples of conducting this assessment. (I am not sure building a [statistical] model on top of the current [physical] models stands a chance to convince climato-skeptics, but this is interesting nonetheless.) Herbie addressed a completely different problem, namely the maximisation of a function under constraints when the constraints are partly unknown. (Think of a set whose boundaries are not precisely known.) This was a problem new to me and I plan to read the paper asap, as the design perspective added to the maximisation per se is made in order to decide about the worth of making new [costly] evaluations of the function to maximise.

Otherwise, the morning was spent in a fruitless pursuit of a wireless connection in the hotel where the conference takes place, as so many people were trying to connect at the same time! I eventually resolved the issue by crossing the road to an internet café and renting an ethernet cable for one hour. The hotel is unsurprisingly the soulless and unhelpful place I expected and I do not find any appeal in the high rise landscape constituting the neighbourhood. There is however a small track in the bush nearby that makes for a good running place in the early morning. (Finding a cliff that is both bolted and in the shade is going to prove a challenge!)