Archive for BayesComp

next BayesComp conference planned for Jan 2018, any volunteer?

Posted in Kids, Mountains, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , , on February 25, 2016 by xi'an

MCMSki III poster, 2010 (C.) IMS[A call from the BayesComp section of ISBA for the next Bayesian computation meeting! As suggested in an earlier post, the label MCMski is discontinued to allow for any location amenable to organise a 200 plus meeting in good and hopefully reasonably priced conditions.]

The Bayesian Computation Section of ISBA is soliciting proposals to host its flagship meeting: BayesComp 2018

The expectation is that the meeting will be held in January 2018, but the committee will consider proposals for other times through January 2019. This meeting is a continuation of the popular MCMSki on recent advances in the theory and application of Bayesian computational methods such as MCMC. The tradition was to hold MCMski meetings in ski resorts, but, as the name change suggests, we encourage applications from any venue that could support BC2018.

A three-day meeting is planned, perhaps with an additional day or two of satellite meetings and/or short courses. One page proposals should address feasibility of hosting the meeting including

1. Proposed dates.
2. Transportation for international participants (both the proximity of international airports and transportation to/from the venue).
3. The conference facilities.
4. The availability and cost of hotels, including low cost options.
5. The proposed local organizing committee and their collective experience organizing international meetings.
6. Expected or promised contributions from the host organization, host country, or industrial partners towards the cost of running the meetings.

Proposals should be submitted to Nicolas Chopin (Program Chair) no later than May 31, 2016. The Board of Bayesian Computing Section will evaluate the proposals, choose a venue, and appoint the Program Committee for BayesComp 2018.

MCMskv #5 [future with a view]

Posted in Kids, Mountains, R, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , on January 12, 2016 by xi'an

As I am flying back to Paris (with an afternoon committee meeting in München in-between), I am reminiscing on the superlative scientific quality of this MCMski meeting, on the novel directions in computational Bayesian statistics exhibited therein, and on the potential settings for the next meeting. If any.

First, as hopefully obvious from my previous entries, I found the scientific program very exciting, with almost uniformly terrific talks, and a coverage of the field of computational Bayesian statistics that is perfectly tuned to my own interest. In that sense, MCMski is my “top one” conference! Even without considering the idyllic location. While some of the talks were about papers I had already read (and commented here), others brought new vistas and ideas. If one theme is to emerge from this meeting it has to be the one of approximate and noisy algorithms, with a wide variety of solutions and approaches to overcome complexity issues. If anything, I wish the solutions would also incorporate the Boxian fact that the statistical models themselves are approximate. Overall, a fantastic program (says one member of the scientific committee).

Second, as with previous MCMski meetings, I again enjoyed the unique ambience of the meeting, which always feels more relaxed and friendly than other conferences of a similar size, maybe because of the après-ski atmosphere or of the special coziness provided by luxurious mountain hotels. This year hotel was particularly pleasant, with non-guests like myself able to partake of some of their facilities. A big thank you to Anto for arranging so meticulously all the details of such a large meeting!!! I am even more grateful when realising this is the third time Anto takes over the heavy load of organising MCMski. Grazie mille!

Since this is a [and even the!] BayesComp conference, the current section program chair and board must decide on the  structure and schedule of the next meeting. A few suggestions if I may: I would scrap entirely the name MCMski from the next conference as (a) it may sound like academic tourism for unaware bystanders (who only need to check the program of any of the MCMski conferences to stand reassured!) and (b) its topic go way beyond MCMC. Given the large attendance and equally large proportion of young researchers, I would also advise against hosting the conference in a ski resort for both cost and accessibility reasons [as we had already discussed after MCMskiv], in favour of a large enough town to offer a reasonable range of accommodations and of travel options. Like Chamonix, Innsbruck, Reykjavik, or any place with a major airport about one hour away… If nothing is available with skiing possibilities, so be it! While the outdoor inclinations of the early organisers induced us to pick locations where skiing over lunch break was a perk, any accessible location that allows for a concentration of researchers in a small area and for the ensuing day-long exchange is fine! Among the novelties in the program, the tutorials and the Breaking news! sessions were quite successful (says one member of the scientific committee). And should be continued in one format or another. Maybe a more programming thread could be added as well… And as we had mentioned earlier, to see a stronger involvement of the Young Bayesian section in the program would be great! (Even though the current meeting already had many young researcher  talks.)

MCMskv, Lenzerheide, 4-7 Jan., 2016 [news #2]

Posted in Mountains, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , on September 7, 2015 by xi'an

moonriseA quick reminder that the early bird registration deadline for BayesComp MCMski V is drawing near. And reminding Og’s readers that there will be a “Breaking news” session to highlight major advances among poster submissions. For which they can apply when sending the poster template. In addition, there is only a limited number of hotel rooms at the Schweizerhof, the main conference hotel and the first 40 participants who will make a reservation there will get a free one-day skipass!

MCMskv, Lenzerheide, 4-7 Jan., 2016 [news #1]

Posted in Kids, Mountains, pictures, R, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , , , on July 20, 2015 by xi'an

moonriseThe BayesComp MCMski V [or MCMskv for short] has now its official website, once again maintained by Merrill Lietchy from Drexel University, Philadelphia, and registration is even open! The call for contributed sessions is now over, while the call for posters remains open until the very end. The novelty from the previous post is that there will be a “Breaking news” [in-between the Late news sessions at JSM and the crash poster talks at machine-learning conferences] session to highlight major advances among poster submissions. And that there will be an opening talk by Steve [the Bayesian] Scott on the 4th, about the frightening prospect of MCMC death!, followed by a round-table and a welcome reception, sponsored by the Swiss Supercomputing Centre. Hence the change in dates. Which still allows for arrivals in Zürich on the January 4th [be with you].

MCMskv, Lenzerheide, Jan. 5-7, 2016

Posted in Kids, Mountains, pictures, R, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , on March 31, 2015 by xi'an

moonriseFollowing the highly successful [authorised opinion!, from objective sources] MCMski IV, in Chamonix last year, the BayesComp section of ISBA has decided in favour of a two-year period, which means the great item of news that next year we will meet again for MCMski V [or MCMskv for short], this time on the snowy slopes of the Swiss town of Lenzerheide, south of Zürich. The committees are headed by the indefatigable Antonietta Mira and Mark Girolami. The plenary speakers have already been contacted and Steve Scott (Google), Steve Fienberg (CMU), David Dunson (Duke), Krys Latuszynski (Warwick), and Tony Lelièvre (Mines, Paris), have agreed to talk. Similarly, the nine invited sessions have been selected and will include Hamiltonian Monte Carlo,  Algorithms for Intractable Problems (ABC included!), Theory of (Ultra)High-Dimensional Bayesian Computation, Bayesian NonParametrics, Bayesian Econometrics,  Quasi Monte Carlo, Statistics of Deep Learning, Uncertainty Quantification in Mathematical Models, and Biostatistics. There will be afternoon tutorials, including a practical session from the Stan team, tutorials for which call is open, poster sessions, a conference dinner at which we will be entertained by the unstoppable Imposteriors. The Richard Tweedie ski race is back as well, with a pair of Blossom skis for the winner!

As in Chamonix, there will be parallel sessions and hence the scientific committee has issued a call for proposals to organise contributed sessions, tutorials and the presentation of posters on particularly timely and exciting areas of research relevant and of current interest to Bayesian Computation. All proposals should be sent to Mark Girolami directly by May the 4th (be with him!).

Robert’s paradox [reading in Reading]

Posted in Statistics, Travel, University life with tags , , , , , , , , , , , , on January 28, 2015 by xi'an

paradoxOn Wednesday afternoon, Richard Everitt and Dennis Prangle organised an RSS workshop in Reading on Bayesian Computation. And invited me to give a talk there, along with John Hemmings, Christophe Andrieu, Marcelo Pereyra, and themselves. Given the proximity between Oxford and Reading, this felt like a neighbourly visit, especially when I realised I could take my bike on the train! John Hemmings gave a presentation on synthetic models for climate change and their evaluation, which could have some connection with Tony O’Hagan’s recent talk in Warwick, Dennis told us about “the lazier ABC” version in connection with his “lazy ABC” paper, [from my very personal view] Marcelo expanded on the Moreau-Yoshida expansion he had presented in Bristol about six months ago, with the notion that using a Gaussian tail regularisation of a super-Gaussian target in a Langevin algorithm could produce better convergence guarantees than the competition, including Hamiltonian Monte Carlo, Luke Kelly spoke about an extension of phylogenetic trees using a notion of lateral transfer, and Richard introduced a notion of biased approximation to Metropolis-Hasting acceptance ratios, notion that I found quite attractive if not completely formalised, as there should be a Monte Carlo equivalent to the improvement brought by biased Bayes estimators over unbiased classical counterparts. (Repeating a remark by Persi Diaconis made more than 20 years ago.) Christophe Andrieu also exposed some recent developments of his on exact approximations à la Andrieu and Roberts (2009).

Since those developments are not yet finalised into an archived document, I will not delve into the details, but I found the results quite impressive and worth exploring, so I am looking forward to the incoming publication. One aspect of the talk which I can comment on is related to the exchange algorithm of Murray et al. (2006). Let me recall that this algorithm handles double intractable problems (i.e., likelihoods with intractable normalising constants like the Ising model), by introducing auxiliary variables with the same distribution as the data given the new value of the parameter and computing an augmented acceptance ratio which expectation is the targeted acceptance ratio and which conveniently removes the unknown normalising constants. This auxiliary scheme produces a random acceptance ratio and hence differs from the exact-approximation MCMC approach, which target directly the intractable likelihood. It somewhat replaces the unknown constant with the density taken at a plausible realisation, hence providing a proper scale. At least for the new value. I wonder if a comparison has been conducted between both versions, the naïve intuition being that the ratio of estimates should be more variable than the estimate of the ratio. More generally, it seemed to me [during the introductory part of Christophe’s talk] that those different methods always faced a harmonic mean danger when being phrased as expectations of ratios, since those ratios were not necessarily squared integrable. And not necessarily bounded. Hence my rather gratuitous suggestion of using other tools than the expectation, like maybe a median, thus circling back to the biased estimators of Richard. (And later cycling back, unscathed, to Reading station!)

On top of the six talks in the afternoon, there was a small poster session during the tea break, where I met Garth Holloway, working in agricultural economics, who happened to be a (unsuspected) fan of mine!, to the point of entitling his poster “Robert’s paradox”!!! The problem covered by this undeserved denomination connected to the bias in Chib’s approximation of the evidence in mixture estimation, a phenomenon that I related to the exchangeability of the component parameters in an earlier paper or set of slides. So “my” paradox is essentially label (un)switching and its consequences. For which I cannot claim any fame! Still, I am looking forward the completed version of this poster to discuss Garth’s solution, but we had a beer together after the talks, drinking to the health of our mutual friend John Deely.

ABC@NIPS: call for papers

Posted in Statistics, Travel, University life with tags , , , , , , , , , on September 9, 2014 by xi'an

In connection with the previous announcement of ABC in Montréal, a call for papers that came out today:

NIPS 2014 Workshop: ABC in Montreal

December 12, 2014
Montréal, Québec, Canada

Approximate Bayesian computation (ABC) or likelihood-free (LF) methods have developed mostly beyond the radar of the machine learning community, but are important tools for a large segment of the scientific community. This is particularly true for systems and population biology, computational psychology, computational chemistry, etc. Recent work has both applied machine learning models and algorithms to general ABC inference (NN, forests, GPs) and ABC inference to machine learning (e.g. using computer graphics to solve computer vision using ABC). In general, however, there is significant room for collaboration between the two communities.

The workshop will consist of invited and contributed talks, poster spotlights, and a poster session. Rather than a panel discussion we will encourage open discussion between the speakers and the audience!

Examples of topics of interest in the workshop include (but are not limited to):

* Applications of ABC to machine learning, e.g., computer vision, inverse problems
* ABC in Systems Biology, Computational Science, etc
* ABC Reinforcement Learning
* Machine learning simulator models, e.g., NN models of simulation responses, GPs etc.
* Selection of sufficient statistics
* Online and post-hoc error
* ABC with very expensive simulations and acceleration methods (surrogate modeling, choice of design/simulation points)
* ABC with probabilistic programming
* Posterior evaluation of scientific problems/interaction with scientists
* Post-computational error assessment
* Impact on resulting ABC inference
* ABC for model selection

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Submission:
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