Archive for CRiSM

Bayesian model comparison with intractable constants

Posted in Books, Kids, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , on February 8, 2016 by xi'an

abcIRichard Everitt, Adam Johansen (Warwick), Ellen Rowing and Melina Evdemon-Hogan have updated [on arXiv] a survey paper on the computation of Bayes factors in the presence of intractable normalising constants. Apparently destined for Statistics and Computing when considering the style. A great entry, in particular for those attending the CRiSM workshop Estimating Constants in a few months!

A question that came to me from reading the introduction to the paper is why a method like Møller et al.’s (2006) auxiliary variable trick should be considered more “exact” than the pseudo-marginal approach of Andrieu and Roberts (2009) since the later can equally be seen as an auxiliary variable approach. The answer was on the next page (!) as it is indeed a special case of Andrieu and Roberts (2009). Murray et al. (2006) also belongs to this group with a product-type importance sampling estimator, based on a sequence of tempered intermediaries… As noted by the authors, there is a whole spectrum of related methods in this area, some of which qualify as exact-approximate, inexact approximate and noisy versions.

Their main argument is to support importance sampling as the method of choice, including sequential Monte Carlo (SMC) for large dimensional parameters. The auxiliary variable of Møller et al.’s (2006) is then part of the importance scheme. In the first toy example, a Poisson is opposed to a Geometric distribution, as in our ABC model choice papers, for which a multiple auxiliary variable approach dominates both ABC and Simon Wood’s synthetic likelihood for a given computing cost. I did not spot which artificial choice was made for the Z(θ)’s in both models, since the constants are entirely known in those densities. A very interesting section of the paper is when envisioning biased approximations to the intractable density. If only because the importance weights are most often biased due to the renormalisation (possibly by resampling). And because the variance derivations are then intractable as well. However, due to this intractability, the paper can only approach the impact of those approximations via empirical experiments. This leads however to the interrogation on how to evaluate the validity of the approximation in settings where truth and even its magnitude are unknown… Cross-validation and bootstrap type evaluations may prove too costly in realistic problems. Using biased solutions thus mostly remains an open problem in my opinion.

The SMC part in the paper is equally interesting if only because it focuses on the data thinning idea studied by Chopin (2002) and many other papers in the recent years. This made me wonder why an alternative relying on a sequence of approximations to the target with tractable normalising constants could not be considered. A whole sequence of auxiliary variable completions sounds highly demanding in terms of computing budget and also requires a corresponding sequence of calibrations. (Now, ABC fares no better since it requires heavy simulations and repeated calibrations, while further exhibiting a damning missing link with the target density. ) Unfortunately, embarking upon a theoretical exploration of the properties of approximate SMC is quite difficult, as shown by the strong assumptions made in the paper to bound the total variation distance to the true target.

CRiSM workshop on estimating constants [#1]

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , on January 19, 2016 by xi'an

The registration for the CRiSM workshop on estimating constants that Nial Friel, Helen Ogden and myself host next April 20-22 at the University of Warwick is now open. The plain registration fees are £40 and accommodation on the campus is available through the same form.

Since besides the invited talks, the workshop will host two poster session with speed (2-5mn) oral presentations, we encourage all interested researchers to submit a poster via the appropriate form. Once again, this should be an exciting two-day workshop, given the on-going activity in this area.

Non-reversible Markov Chains for Monte Carlo sampling

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , on September 24, 2015 by xi'an

the pond in front of the Zeeman building, University of Warwick, July 01, 2014This “week in Warwick” was not chosen at random as I was aware there is a workshop on non-reversible MCMC going on. (Even though CRiSM sponsored so many workshops in September that almost any week would have worked for the above sentence!) It has always been kind of a mystery to me that non-reversibility could make a massive difference in practice, even though I am quite aware that it does. And I can grasp some of the theoretical arguments why it does. So it was quite rewarding to sit in this Warwick amphitheatre and learn about overdamped Langevin algorithms and other non-reversible diffusions, to see results where convergence times moved from n to √n, and to grasp some of the appeal of lifting albeit in finite state spaces. Plus, the cartoon presentation of Hamiltonian Monte Carlo by Michael Betancourt was a great moment, not only because of the satellite bursting into flames on the screen but also because it gave a very welcome intuition about why reversibility was inefficient and HMC appealing. So I am grateful to my two colleagues, Joris Bierkens and Gareth Roberts, for organising this exciting workshop, with a most profitable scheduling favouring long and few talks. My next visit to Warwick will also coincide with a workshop on intractable likelihood, next November. This time part of the new Alan Turing Institute programme.

AISTATS 2016 [call for submissions]

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , on August 21, 2015 by xi'an

At the last (European) AISTATS 2014, I agreed to be the program co-chair for AISTATS 2016, along with Arthur Gretton from the Gatsby Unit, at UCL. (AISTATS stands for Artificial Intelligence and Statistics.) Thanks to Arthur’s efforts and dedication, as the organisation of an AISTATS meeting is far more complex than any conference I have organised so far!, the meeting is taking shape. First, it will take place in Cadiz, Andalucía, Spain, on May 9-11, 2016. (A place more related to the conference palm tree logo than the previous location in Reykjavik, even though I would be the last one to complain it took place in Iceland!)

Second, the call for submissions is now open. The process is similar to other machine learning conferences in that papers are first submitted for the conference proceedings, then undergo a severe and tight reviewing process, with a response period for the authors to respond to the reviewers’ comments, and that only the accepted papers can be presented as posters, some of which are selected for an additional oral presentation. The major dates for submitting to AISTATS 2016 are

Proceedings track paper submission deadline 23:59UTC Oct 9, 2015
Proceedings track initial reviews available Nov 16, 2015
Proceedings track author feedback deadline Nov 23, 2015
Proceedings track paper decision notifications Dec 20, 2015

With submission instructions available at this address. Including the electronic submission site.

I was quite impressed by the quality and intensity of the AISTATS 2014 conference, which is why I accepted so readily being program co-chair, and hence predict an equally rewarding AISTATS 2016, thus encouraging all interested ‘Og’s readers to consider submitting a paper there! Even though I confess it will make a rather busy first semester for 2016, between MCMSki V in January, the CIRM Statistics month in February, the CRiSM workshop on Eatimating constants in April, AISTATS 2016 thus in May, and ISBA 2016 in June…

on estimating constants…

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , on July 21, 2015 by xi'an

While I discussed on the ‘Og in the past the difference I saw between estimating an unknown parameter from a distribution and evaluating a normalising constant, evaluating such constants and hence handling [properly] doubly intractable models is obviously of the utmost importance! For this reason, Nial Friel, Helen Ogden and myself have put together a CRiSM workshop on the topic (with the tongue-in-cheek title of Estimating constants!), to be held at the University of Warwick next April 20-22.

The CRiSM workshop will focus on computational methods for approximating challenging normalising constants found in Monte Carlo, likelihood and Bayesian models. Such methods may be used in a wide range of problems: to compute intractable likelihoods, to find the evidence in Bayesian model selection, and to compute the partition function in Physics. The meeting will bring together different communities working on these related problems, some of which have developed original if little advertised solutions. It will also highlight the novel challenges associated with large data and highly complex models. Besides a dozen invited talks, the schedule will highlight two afternoon poster sessions with speed (2-5mn) oral presentations called ‘Elevator’ talks.

While 2016 is going to be quite busy with all kinds of meetings (MCMSkv, ISBA 2016, the CIRM Statistics month, AISTATS 2016, …), this should be an exciting two-day workshop, given the on-going activity in this area, and I thus suggest interested readers to mark the dates in their diary. I will obviously keep you posted about registration and accommodation when those entries are available.

probabilistic numerics

Posted in pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , on April 27, 2015 by xi'an

sunwar2I attended an highly unusual workshop while in Warwick last week. Unusual for me, obviously. It was about probabilistic numerics, i.e., the use of probabilistic or stochastic arguments in the numerical resolution of (possibly) deterministic problems. The notion in this approach is fairly Bayesian in that it makes use to prior information or belief about the quantity of interest, e.g., a function, to construct an usually Gaussian process prior and derive both an estimator that is identical to a numerical method (e.g., Runge-Kutta or trapezoidal integration) and uncertainty or variability around this estimator. While I did not grasp much more than the classy introduction talk by Philipp Hennig, this concept sounds fairly interesting, if only because of the Bayesian connection, and I wonder if we will soon see a probability numerics section at ISBA! More seriously, placing priors on functions or functionals is a highly formal perspective (as in Bayesian non-parametrics) and it makes me wonder how much of the data (evaluation of a function at a given set of points) and how much of the prior is reflected in the output [variability]. (Obviously, one could also ask a similar question for statistical analyses!)  For instance, issues of singularity arise among those stochastic process priors.

Another question that stemmed from this talk is whether or not more efficient numerical methods can derived that way, in addition to recovering the most classical ones. Somewhat, somehow, given the idealised nature of the prior, it feels like priors could be more easily compared or ranked than in classical statistical problems. Since the aim is to figure out the value of an integral or the solution to an ODE. (Or maybe not, since again almost the same could be said about estimating a normal mean.)

travellin’ week ahead

Posted in Books, Statistics, Travel, University life with tags , , , , , , , , on November 24, 2013 by xi'an

London by Delta, Dec. 14, 2011Next week is my week at the University of Warwick, where I will give a seminar at the CRiSM seminar on Thursday. Along with my friend Olli Ratmann. Except that I also got invited at the Luxembourg annual statistics conference the same week, meaning I will travel to Luxembourg on Wednesday to give my talk. (First time ever.) And the easiest way from Coventry is to fly thru Paris. In preparation for this travelling schedule bordering the insane, I printed a whole heap of arXiv publications… Keep posted!

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