Archive for ICERM

oops, no tooltip…!

Posted in pictures with tags , , , , on January 29, 2013 by xi'an

Thanks to Jean-Michel Marin, I have just noticed that the legends I put on my (or others‘) images were not visible as blue boxes hovering over the picture. I checked on wordpress and found the solution: The new title of the downloaded image is not the title of the published image!

The title added in this field does not display as a tooltip (when a mouse is hovered over the image). To add a tooltip title, edit the image after inserting it into the post, and add your tooltip wording to the Title field.

However that means that the older images in the ‘Og (those published since the new version of wordpress was implemented, around the very end of November…) will not be corrected…

estimating the measure and hence the constant

Posted in pictures, Running, Statistics, University life with tags , , , , , , , on December 6, 2012 by xi'an

Dawn in Providence, Nov. 30, 2012As mentioned on my post about the final day of the ICERM workshop, Xiao-Li Meng addresses this issue of “estimating the constant” in his talk. It is even his central theme. Here are his (2011) slides as he sent them to me (with permission to post them!):

He therefore points out in slide #5 why the likelihood cannot be expressed in terms of the normalising constant because this is not a free parameter. Right! His explanation for the approximation of the unknown constant is then to replace the known but intractable dominating measure—in the sense that it cannot compute the integral—with a discrete (or non-parametric) measure supported by the sample. Because the measure is defined up to a constant, this leads to sample weights being proportional to the inverse density. Of course, this representation of the problem is open to criticism: why focus only on measures supported by the sample? The fact that it is the MLE is used as an argument in Xiao-Li’s talk, but this can alternatively be seen as a drawback: I remember reviewing Dankmar Böhning’s Computer-Assisted Analysis of Mixtures and being horrified when discovering this feature! I am currently more agnostic since this appears as an alternative version of empirical likelihood. There are still questions about the measure estimation principle: for instance, when handling several samples from several distributions, why should they all contribute to a single estimate of μ rather than to a product of measures? (Maybe because their models are all dominated by the same measure μ.) Now, getting back to my earlier remark, and as a possible answer to Larry’s quesiton, there could well be a Bayesian version of the above, avoiding the rough empirical likelihood via Gaussian or Drichlet process prior modelling.

ICERM, Brown, Providence, RI (#3)

Posted in pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , on December 3, 2012 by xi'an

ICERM building, Providence, RI, Nov. 29, 2012Just yet another perfect day in Providence! Especially when I thought it was going to be a half-day: After a longer and slightly warmer run in the early morning around the peninsula, I attended the lecture by Eric Moulines on his recent results on adaptive MCMC and the equi-energy sampler. At this point, we were told that, since Peter Glynn was sick, the afternoon talks were drifted forward. This meant that I could attend Mylène Bédard’s talk in the morning and most of Xiao-Li Meng’s talk, before catching my bus to the airport, making it a full day in the end!

The research presented by Mylène (and coauthored with Randal Douc and Eric Moulines) was on multiple-try MCMC and delayed-rejection MCMC, with optimal scaling results and a comparison of the efficiency of those involved schemes. I had not seen the work before and got quite impressed by the precision of the results and the potential for huge efficiency gains. One of the most interesting tricks was to use an antithetic move for the second step, considerably improving the acceptance rate in the process. An aside exciting point was to realise that the hit-and-run solution was also open to wide time-savings thanks to some factorisation.

DSC_3532While Xiao-Li’s talk had connections with his earlier illuminating talk in New York last year, I am quite desolate to have missed [the most novel] half of it (and still caught my bus by a two minute margin!), esp. because it connected beautifully with the constant estimation controverse! Indeed, Xiao-Li started his presentation with the pseudo-paradox that the likelihood cannot be written as a function of the normalising constant, simply because this is not a free parameter. He then switched to his usual theme that the dominating measure was to be replaced with a substitute and estimated.The normalising constant being a function of the dominating measure, it is a by-product of this estimation step. And can even be endowed within a Bayesian framework. Obviously, one can always argue against the fact that the dominating measure is truly unknown, however this gives a very elegant safe-conduct to escape the debate about the constant that did not want to be estimated…So to answer Xiao-Li’s question as I was leaving the conference room, I have now come to a more complete agreement with his approach. And think further advances could be contemplated along this path…

ICERM, Brown, Providence, RI (#2)

Posted in pictures, Running, Statistics, Travel, University life with tags , , , , , , , on November 30, 2012 by xi'an

ICERM building by the canal, Providence, RI, Nov. 29, 2012Just another perfect day in Providence! After a brisk run in the eearly morning which took me through Brown campus, I attended the lecture by Sean Meyn on feedback particle filters. As it was mostly on diffusions with control terms, just too far from my field, I missed most of the points. (My fault, not Sean’s!) Then Ramon von Handel gave a talk about the curse(s) of dimensionality in particle filters, much closer to my interests, with a good summary of why (optimal) filters were not suffering from a curse in n, the horizon size, but in d, the dimension of the space, followed by an argument that some degree of correlation decay could overcome this dimensional curse as well. After the lunch break (where I thought further about the likelihood principle!), Dana Randall gave a technical talk on mixing properties of the hardcore model on Z² and bounding the cutoff parameter, which is when I appreciated the ability to follow talks from the ICERM lounge, watching slides and video of the talk taking place on the other side of the wall! At last, and in a programming contrapoint from slowly mixing to fastest mixing, Jim Fill presented his recent work on ordering Markov chains and finding fastest-mixing chains, which of course reminded me of Peskun ordering although there may be little connection in the end. The poster session in the evening had sufficiently few posters to make the discussion with each author enjoyable and relevant.A consistent feature of the meeting thus, allowing for quality interacting time between participants. I am now looking forward the final day with a most intriguing title by my friend Eric Moulines on TBA…

ICERM, Brown, Providence, RI (#1)

Posted in Statistics, Travel, University life with tags , , , , on November 29, 2012 by xi'an

As I mentioned yesterday, and earlier, I was rather excited by the visit of the ICERM building. As it happens, the centre is located at the upper floor of a (rather bland!) 11 floor building sitting between Main St. and the river. It is quite impressive indeed, with a feeling of space due to the high ceilings and the glass walls all around the conference room, plus pockets of quietness with blackboards at the rescue. The whiteboard that makes the wall between the conference room and the lobby is also appreciable for discussion as it is huge (the whole wall is the whiteboard!) and made of a glassy material that makes writing on it a true pleasure (the next step would be to have a recording device embedded in it!). When I gave my talk and attended the other three talks of the day, I kind of regretted that the dual projector system would not allow for a lag of sorts in the presentation. Even though the pace of the other talks was quite reasonable (mine was a bit hurried I am afraid!), writing down a few notes was enough for me to miss some point from the previous slide. With huge walls, it should be easy to project at least the previous slide at the same time and maybe even all of the previous slide (maybe, maybe not, as it would get quickly confusing…)

Paul Dupuis’ talk covered new material (at least for me) on importance sampling for diffusions and the exploration of equilibriums, and it was thus quite enjoyable, even when fighting one of my dozing attacks. Gareth Roberts’ talk provided a very broad picture of the different optimal scalings (à la 0.234!) for MCMC algorithms (while I have attended several lectures by Gareth on this theme, there is always something new and interesting coming out of them!). Krzysztof Latuszynski’s talk on irreducible diffusions and the construction of importance sampling solutions replacing the (unavailable) exact sampling of Beskos et al. (2006) led to some discussion on the handling of negative weights. This is a question that has always intrigued me: if unbiasedness or exact simulation or something else induce negative weights in a sample, how can we process those weights when resampling? The conclusion of the discussion was that truncating the weights to zero seemed like the best solution, at least when resampling since the weights can be used as such in averages, but I wonder if there is a more elaborate scheme involving mixtures or whatnot!

ICERM, Brown, Providence, RI (#0)

Posted in Running, Statistics, Travel, University life with tags , , , , , , , , on November 28, 2012 by xi'an

I have just arrived in Providence, RI, for the ICERM workshop on Performance Analysis of Monte Carlo Methods. While the plane trip was uneventful and even relaxing, as I could work on the revision to our ABCel (soon to be BCel!) paper, the bus trip from Boston to Providence, while smooth, quiet, wirelessed, and on-time, was a wee too much as it was already late for my standards… Anyway, I am giving one of the talks tomorrow, with a pot-pourri on ABC and empirical likelihood as in Ames and Chicago last month. The format of the workshop sounds very nice, with only four talks a day, which should leave a lot of space for interactions between participants (if I do not crash from my early early rise…) And, as mentioned earlier, I am looking forward visiting the futuristic building.

Computational Challenges in Probability [ICERM, Sept. 5 – Dec. 7]

Posted in Statistics, Travel, University life with tags , , , , , , , , , on May 18, 2012 by xi'an

I have just received an invitation to take part in the program “Computational Challenges in Probability” organised by ICERM (Institute for Computational and Experimental Research in Mathematics, located in what sounds like a terrific building!) next semester. Here is the purpose statement:

The Fall 2012 Semester on “Computational Challenges in Probability” aims to bring together leading experts and young researchers who are advancing the use of probabilistic and computational methods to study complex models in a variety of fields. The goal is to identify common challenges, exchange existing tools, reveal new application areas and forge new collaborative efforts. The semester includes four workshops – Bayesian Nonparametrics, Uncertainty Quantification, Monte Carlo Methods in the Physical and Biological Sciences and Performance Analysis of Monte Carlo Methods. In addition, synergistic activities will be planned throughout the duration of the semester. In particular, there will be several short courses and plenary invited talks by experts on related topics such as graphical models, randomized algorithms and stochastic networks, regular weekly seminars and relevant film screenings.

There are thus four workshops organised over the period and an impressive collection of long-term participants. I will most likely take part in the last workshop, “Performance Analysis of Monte Carlo Methods”, although I would like to attend all of them! (Interesting side remark: while looking at the ICERM website, I found that May 18th is the Day of Data! Great, except that neither the word statistitics nor the word statistician appear on the page…)