Archive for the Wines Category
This week in Warwick was one of the busiest ones ever as I had to juggle between two workshops, including one in Oxford, a departmental meeting, two paper revisions, two pre-vivas, and a seminar in Leeds. Not to mention a broken toe (!), a flat tire (!!), and a diner at the X. Hardly anytime for writing blog entries..! Fortunately, I managed to squeeze time for working with Kerrie Mengersen who was visiting Warwick this fortnight. Finding new directions for the (A)BCel approach we developed a few years ago with Pierre Pudlo. The workshop in Oxford was quite informal with talks from PhD students [I fear I cannot discuss here as the papers are not online yet]. And one talk by François Caron about estimating sparse networks with not exactly exchangeable priors and completely random measures. And one talk by Kerrie Mengersen on a new and in-progress approach to handling Big Data that I found quite convincing (if again cannot discuss here). The probabilistic numerics workshop was discussed in yesterday’s post and I managed to discuss it a wee bit further with the organisers at The X restaurant in Kenilworth. (As a superfluous aside, and after a second sampling this year, I concluded that the Michelin star somewhat undeserved in that the dishes at The X are not particularly imaginative or tasty, the excellent sourdough bread being the best part of the meal!) I was expecting the train ride to Leeds to be highly bucolic as it went through the sunny countryside of South Yorkshire, with newly born lambs running in the bright green fields surrounded by old stone walls…, but instead went through endless villages with their rows of brick houses. Not that I have anything against brick houses, mind! Only, I had not realised how dense this part of England was, this presumably getting back all the way to the Industrial Revolution with the Manchester-Leeds-Birmingham triangle.
My seminar in Leeds was as exciting as in Amsterdam last week and with a large audience, so I got many and only interesting questions, from the issue of turning the output (i.e., the posterior on α) into a decision rule, to making decision in the event of a non-conclusive posterior, to links with earlier frequentist resolutions, to whether or not we were able to solve the Lindley-Jeffreys paradox (we are not!, which makes a lot of sense), to the possibility of running a subjective or a sequential version. After the seminar I enjoyed a perfect Indian dinner at Aagrah, apparently a Yorkshire institution, with the right balance between too hot and too mild, i.e., enough spices to break a good sweat but not too many to loose any sense of taste!
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.
On Monday, I went to Amsterdam to give a seminar at the University of Amsterdam, in the department of psychology. And to visit Eric-Jan Wagenmakers and his group there. And I had a fantastic time! I talked about our mixture proposal for Bayesian testing and model choice without getting hostile or adverse reactions from the audience, quite the opposite as we later discussed this new notion for several hours in the café across the street. I also had the opportunity to meet with Peter Grünwald [who authored a book on the minimum description length principle] pointed out a minor inconsistency of the common parameter approach, namely that the Jeffreys prior on the first model did not have to coincide with the Jeffreys prior on the second model. (The Jeffreys prior for the mixture being unavailable.) He also wondered about a more conservative property of the approach, compared with the Bayes factor, in the sense that the non-null parameter could get closer to the null-parameter while still being identifiable.
Among the many persons I met in the department, Maarten Marsman talked to me about his thesis research, Plausible values in statistical inference, which involved handling the Ising model [a non-sparse Ising model with O(p²) parameters] by an auxiliary representation due to Marc Kac and getting rid of the normalising (partition) constant by the way. (Warning, some approximations involved!) And who showed me a simple probit example of the Gibbs sampler getting stuck as the sample size n grows. Simply because the uniform conditional distribution on the parameter concentrates faster (in 1/n) than the posterior (in 1/√n). This does not come as a complete surprise as data augmentation operates in an n-dimensional space. Hence it requires more time to get around. As a side remark [still worth printing!], Maarten dedicated his thesis as “To my favourite random variables , Siem en Fem, and to my normalizing constant, Esther”, from which I hope you can spot the influence of at least two of my book dedications! As I left Amsterdam on Tuesday, I had time for a enjoyable dinner with E-J’s group, an equally enjoyable early morning run [with perfect skies for sunrise pictures!], and more discussions in the department. Including a presentation of the new (delicious?!) Bayesian software developed there, JASP, which aims at non-specialists [i.e., researchers unable to code in R, BUGS, or, God forbid!, STAN] And about the consequences of mixture testing in some psychological experiments. Once again, a fantastic time discussing Bayesian statistics and their applications, with a group of dedicated and enthusiastic Bayesians!
Jean-Michel Marin, Pierre Pudlo and I just arXived a short review on ABC model choice, first version of a chapter for the incoming Handbook of Approximate Bayesian computation edited by Scott Sisson, Yannan Fan, and Mark Beaumont. Except for a new analysis of a Human evolution scenario, this survey mostly argues for the proposal made in our recent paper on the use of random forests and [also argues] about the lack of reliable approximations to posterior probabilities. (Paper that was rejected by PNAS and that is about to be resubmitted. Hopefully with a more positive outcome.) The conclusion of the survey is that
The presumably most pessimistic conclusion of this study is that the connections between (i) the true posterior probability of a model, (ii) the ABC version of this probability, and (iii) the random forest version of the above, are at best very loose. This leaves open queries for acceptable approximations of (i), since the posterior predictive error is instead an error assessment for the ABC RF model choice procedure. While a Bayesian quantity that can be computed at little extra cost, it does not necessarily compete with the posterior probability of a model.
reflecting my hope that we can eventually come up with a proper approximation to the “true” posterior probability…