Among several interesting (general public) entries and the fascinating article reconstituting the death of Lucy by a fall from a tree, I spotted in the current Sept. 22 issue of Nature two short summaries involving statistical significance, one in linguistics about repeated (and significant) links between some sounds and some concepts (like ‘n’ and ‘nose’) shared between independent languages, another about the (significant) discovery of a π meson and a K meson. The first anonymous editorial, entitled “Algorithm and blues“, was rather gloomy about the impact of proprietary algorithms on our daily life and on our democracies (or what is left of them), like the reliance on such algorithms to grant loan or determining the length of a sentence (based on the estimated probability of re-offending). The article called for more accountability of such tools, from going completely open-source to allowing for some form of strong auditing. This reminded me of the current (regional) debate about the algorithm allocating Greater Paris high school students to local universities and colleges based on their grades, wishes, and available positions. The apparent randomness and arbitrariness of those allocations prompted many (parents) to complain about the algorithm and ask for its move to the open. (Besides the pun in the title, the paper also contained a line about “affirmative algorithmic action”!) There was also a perfectly irrelevant tribune from a representative of the Church of England about its desire to give a higher profile to science in the/their church. Whatever. And I also was bemused by a news article on the difficulty to build a genetic map of Australia Aboriginals due to cultural reticence of Aboriginals to the use of body parts from their communities in genetic research. While I understand and agree with the concept of data privacy, so that to restrain to expose personal information, it is much less clear [to me] why data collected a century ago should come under such protections if it does not create a risk of exposing living individuals. It reminded me of this earlier Nature news article about North-America Aboriginals claiming right to a 8,000 year old skeleton. On a more positive side, this news part also mentioned the first catalogue produced by the Gaia European Space Agency project, from the publication of more than a billion star positions to the open access nature of the database, in that the Gaia team had hardly any prior access to such wealth of data. A special issue part of the journal was dedicated to the impact of social inequalities in the production of (future) scientists, but this sounds rather shallow, at least at the level of the few pages produced on the topic and it did not mention a comparison with other areas of society, where they are also most obviously at work!
Archive for algorithms
[verbatim from the call for papers:]
Statistics and Computing is preparing a special issue on Bayesian Nonparametrics, for publication by early 2016. We invite researchers to submit manuscripts for publication in the special issue. We expect that the focus theme will increase the visibility and impact of papers in the volume.
By making use of infinite-dimensional mathematical structures, Bayesian nonparametric statistics allows the complexity of a learned model to grow as the size of a data set grows. This flexibility can be particularly suited to modern data sets but can also present a number of computational and modelling challenges. In this special issue, we will showcase novel applications of Bayesian nonparametric models, new computational tools and algorithms for learning these models, and new models for the diverse structures and relations that may be present in data.
To submit to the special issue, please use the Statistics and Computing online submission system. To indicate consideration for the special issue, choose “Special Issue: Bayesian Nonparametrics” as the article type. Papers must be prepared in accordance with the Statistics and Computing journal guidelines.
Papers will go through the usual peer review process. The special issue website will be updated with any relevant deadlines and information.
Deadline for manuscript submission: August 20, 2015
Surrounding the great and exciting gathering of Bayesian statisticians in Kyoto last June, several ISBA sections have appeared in the past weeks, as already mentioned on the ‘Og. Along with Anto Mira and Nicolas Chopin (who did most of the organisational work while I was wandering down under!), we discussed about a Bayesian computation section and, thanks to the massive support of the community, we engaged into setting this new section of ISBA, with the help of Peter Green and Håvard Rue. The structure has now been granted an approval stamp by the ISBA highest powers and so here we are with a brand new ISBA Section on Bayesian Computation!!! (A notion I remember discussing with Peter Müller in Valparaiso in…2004!) I think I was the first member to join the section, following the announcement of its official creation by Merlise Clyde… Here is a draft of the call to potential members (along with my own comments):
Over the past twenty years, Bayesian computation has been a tremendous catalyst in Bayesian ideas reaching practitioners – statisticians and non-statisticians alike. It has also providied a fantastic arena for original research in algorithmic statistics and numerical probability, not to mention other fields at the interface. At this more mature stage of its development, at a time where ambitions of statisticians and the expectations on statistics grow, Bayesian computation must remain a major area of research and innovation. Then principled methods of statistical analysis can continue to be both readily available and customarily implemented, as we deal with data on a (much) larger scale, in higher dimensions and with more complex structure.
We invite all ISBA members with (any degree of) interest in computation for Bayesian inference to join the newly created ISBA Section on Bayesian Computation (BayesComp) – and that means both researchers involved in developing new computational methods and associated theory, and users of Bayesian statistical methods interested in implementing, sharing, disseminating, or learning best practice. The purposes of the Section are as multifaceted as the aspects of Bayesian computation, including promoting original research into computational methods for Bayesian inference and decision making, encouraging the use of frontier computational tools among practitioners, the development of adapted software, languages, platforms, and dedicated machines, and translating and disseminating among statisticians methods developed in other disciplines.
To address these purposes, the Section will among other activities organise specific conferences (such as the upcoming MCMSki IV in January 2014), workshops, short courses, webinars, and sessions in other meetings like ISBA and JSM, and will develop and maintain a website of information, tools, and advice as an authoritative central resource for Bayesian computation. The first such resource is already posted: the ISBA Foundation Lecture by Christian Robert on “Approximate Bayesian computation (ABC): Advances and Questions.”[I am definitely not responsible for this inclusion!]
Section dues are only $5 a year or $75 for a Lifetime membership. As part of the Fall (Autumn) Membership Promotion, all new annual memberships will be extended until 31 December, 2013! The section will be holding elections in November, so please join today so that you may participate in choosing the first set of elected officers–and please contact us if you are interested in any of the elected positions! More details to come on the BayesComp section website and the ISBA Bulletin. [You should definitely opt for the Life membership as I did, given that the transaction costs are paid only once! This also means more money for the Section to support younger members towards travel to conferences…]
Welcome to Year 1 BC (BayesComp)!
Nicolas Chopin, Peter Green, Antonietta Mira, Christian Robert and Håvard Rue.