Archive for Alan Turing Institute

missing bit?

Posted in Books, Statistics, University life with tags , , , , , , , , on January 9, 2021 by xi'an

Nature of 7 December 2020 has a Nature Index (a supplement made of a series of articles, more journalistic than scientific, with corporate backup, which “have no influence over the content”) on Artificial Intelligence, including the above graph representing “the top 200 collaborations among 146 institutions based between 2015 and 2019, sized according to each institution’s share in artificial intelligence”, with only the UK, Germany, Switzerland and Italy identified for Europe… Missing e.g. the output from France and from its major computer science institute, INRIA. Maybe because “the articles picked up by [their] database search concern specific applications of AI in the life sciences, physical sciences, chemistry, and Earth and environmental sciences”.  Or maybe because of the identification of INRIA as such.

“Access to massive data sets on which to train machine-learning systems is one advantage that both the US and China have. Europe, on the other hand, has stringent data laws, which protect people’s privacy, but limit its resources for training AI algorithms. So, it seems unlikely that Europe will produce very sophisticated AI as a consequence”

This comment is sort of contradictory for the attached articles calling for a more ethical AI. Like making AI more transparent and robust. While having unrestricted access to personal is helping with social engineering and control favoured by dictatures and corporate behemoths, a culture of data privacy may (and should) lead to develop new methodology to work with protected data (as in an Alan Turing Institute project) and to infuse more trust from the public. Working with less data does not mean less sophistication in handling it but on the opposite! Another clash of events appears in one of the six trailblazers portrayed in the special supplement being Timnit Gebru, “former co-lead of the Ethical AI Team at Google”, who parted way with Google at the time the issue was published. (See Andrew’s blog for  discussion of her firing. And the MIT Technology Review for an analysis of the paper potentially at the source of it.)

postdoc at Warwick on robust SMC [call]

Posted in Kids, pictures, R, Statistics, University life with tags , , , , , , , , on January 11, 2020 by xi'an

Here is a call for a research fellow at the University of Warwick to work with Adam Johansen and Théo Damoulas on the EPSRC and Lloyds Register Foundaton funded project “Robust Scalable Sequential Monte Carlo with application to Urban Air Quality”. To quote

The position will be based primarily at the Department of Statistics of the University of Warwick. The post holder will work closely in collaboration with the rest of the project team and another postdoctoral researcher to be recruited shortly to work within the Data Centric Engineering programme at the Alan Turing Institute in London. The post holder will be expected to visit the Alan Turing Institute regularly.

Candidates with strong backgrounds in the mathematical analysis of stochastic algorithms or sequential Monte Carlo methods are particularly encouraged to apply. Closing date is 19 Jan 2020.

we need to talk about statistics

Posted in pictures, Statistics, University life with tags , , , , on July 17, 2019 by xi'an

another instance of a summer of Bayesian conferences

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , on March 15, 2018 by xi'an

As it happens, the next MaxEnt conference will happens in London, on 2-6 July, at the Alan Turing Institute, which makes it another perfect continuation of the ISBA meeting in Edinburgh, or of the Computational Statistics summer school in Warwick the week after. But in competition with BAYsm in Warwick and MCqMC in Rennes. I once attended a MaxEnt meeting in Oxford. (Oxford, Mississippi!) Which was quite interesting in the audience it attracted and the focus of the discussions, some of which were exhilaratingly philosophical!

pseudo slice sampling

Posted in Books, Statistics, University life with tags , , , , , on November 26, 2015 by xi'an

The workshop in Warwick last week made me aware of (yet) another arXiv posting I had missed: Pseudo-marginal slice sampling by Iain Murray and Matthew Graham. The idea is to mix the pseudo-marginal approach of Andrieu and Roberts (2009) with a noisy slice sampling scheme à la Neal (2003). The auxiliary random variable u used in the (pseudo-marginal) unbiased estimator of the target I(θ), Î(θ,u), and with distribution q(u) is merged with the random variable of interest so that the joint is

Î(θ,u)q(u)/C

and a Metropolis-Hastings proposal on that target simulating from k(θ,θ’)q(u’) [meaning the auxiliary is simulated independently] recovers the pseudo-marginal Metropolis-Hastings ratio

Î(θ’,u‘)k(θ’,θ)/Î(θ,u)k(θ,θ’)

(which is a nice alternative proof that the method works!). The novel idea in the paper is that the proposal on the auxiliary u can be of a different form, while remaining manageable. For instance, as a two-block Gibbs sampler. Or an elliptical slice sampler for the u component. The argument being that an independent update of u may lead the joint chain to get stuck. Among the illustrations in the paper, an Ising model (with no phase transition issue?) and a Gaussian process applied to the Pima Indian data set (despite a recent prohibition!). From the final discussion, I gather that the modification should be applicable to every (?) case when a pseudo-marginal approach is available, since the auxiliary distribution q(u) is treated as a black box. Quite an interesting read and proposal!