Archive for scientific journals

AISTATS 2016 [post-decisions]

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

Now that the (extended) deadline for AISTATS 2016 decisions is gone, I can gladly report that out of 594 submissions, we accepted 165 papers, including 35 oral presentations. As reported in the previous blog post, I remain amazed at the gruesome efficiency of the processing machinery and at the overwhelmingly intense involvement of the various actors who handled those submissions. And at the help brought by the Toronto Paper Matching System, developed by Laurent Charlin and Richard Zemel. I clearly was not as active and responsive as many of those actors and definitely not [and by far] as my co-program-chair, Arthur Gretton, who deserves all the praise for achieving a final decision by the end of the year. We have already received a few complaints from rejected authors, but this is to be expected with a rejection rate of 73%. (More annoying were the emails asking for our decisions in the very final days…) An amazing and humbling experience for me, truly! See you in Cadiz, hopefully.

AISTATS 2016 [post-submissions]

Posted in Books, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , on October 22, 2015 by xi'an

Now that the deadline for AISTATS 2016 submissions is past, I can gladly report that we got the amazing number of 559 submissions, which is much more than what was submitted to the previous AISTATS conferences. To the point it made us fear for a little while [but not any longer!] that the conference room was not large enough. And hope that we had to install video connections in the hotel bar!

Which also means handling about the same amount of papers as a year of JRSS B submissions within a single month!, the way those submissions are handled for the AISTATS 2016 conference proceedings. The process is indeed [as in other machine learning conferences] to allocate papers to associate editors [or meta-reviewers or area chairs] with a bunch of papers and then have those AEs allocate papers to reviewers, all this within a few days, as the reviews have to be returned to authors within a month, for November 16 to be precise. This sounds like a daunting task but it proceeded rather smoothly due to a high degree of automation (this is machine-learning, after all!) in processing those papers, thanks to (a) the immediate response to the large majority of AEs and reviewers involved, who bid on the papers that were of most interest to them, and (b) a computer program called the Toronto Paper Matching System, developed by Laurent Charlin and Richard Zemel. Which tremendously helps with managing about everything! Even when accounting for the more formatted entries in such proceedings (with an 8 page limit) and the call to the conference participants for reviewing other papers, I remain amazed at the resulting difference in the time scales for handling papers in the fields of statistics and machine-learning. (There was a short lived attempt to replicate this type of processing for the Annals of Statistics, if I remember well.)

“la formule qui décrypte le monde”

Posted in Books, Statistics, University life with tags , , , , , , , on November 6, 2012 by xi'an

“It is only in the 1980s that the American mathematician Judea Pearl has shown that, by aligning hundreds of Bayes formulas, it was possible to take into account the multiple causes of a complex phenomenon.” (my translation)

As a curious coincidence, the latest issue of Science & Vie appeared on the day I was posting about Peter Coles’s warnings on scientific communication. The cover title of the magazine is the title of this post, The formula decrypting the World, and it is of course about… Bayes’ formula, no-one else’s!!! The major section (16 pages) in this French scientific vulgarization magazine is indeed dedicated to Bayesian statistics and even more Bayesian networks, with the usual stylistic excesses of journalism. As it happens, one of the journalists in charge of this issue came to discuss the topic with me a long while ago in Paris-Dauphine and I remember the experience as being not particularly pleasant since I had trouble communicating the ideas of Bayesian statistics in layman terms. In the end, this rather lengthy interview produced two quotes from me, one that could be mine (in connection with some sentences from Henri Poincaré) and another that is definitely apocryphal (yes, indeed, the one above! I am adamant I could not have mentioned Judea Pearl, whose work I am not familiar with, and even less this bizarre image of hundreds of Bayes’ theorems… Presumably, this got mixed up with a quote from another interviewed Bayesian. The same misquoting occurred for my friend Jean-Michel Marin!).

Among the illustrations selected in the journal as vignettes, the Monty Hall paradox—which is an exercise in conditioning, not in statistical reasoning!—, signal processing for microscope images, Bayesian networks for robots, population genetics (and the return of the musk ox!), stellar cloud formation, tsunami prediction, microarray analysis, climate meta-analysis (with a quote from Noel Cressie), post-Higgs particle physics, ESP studies invalidation by Wagenmakers (missing the fact that the reply by Bern, Utts, and Johnson is equally Bayesian), quantum physics. From a more remote perspective, those are scientific studies using Bayesian statistics to establish important and novel results. However, it would have been easy to come up with equally important and novel results demonstrated via classical non-Bayesian approaches, such as exhibiting the Higgs boson. Now, I understand the difficulty in conveying to the layman the difference resulting from using a Bayesian reasoning to support a scientific argument, however this accumulation of superlatives opens the door to suspicions of bias and truncated perspectives… The second half of the report is less about statistics and more about psychology and learning, expanding on the notion that the brain operates in ways similar to Bayesian learning and networks. Continue reading

In praise of the referee (2)

Posted in Statistics, University life with tags , , , , , , on May 24, 2012 by xi'an

Following Nicolas’ guest-post on this ‘Og, plus Andrew’s and mine’s, we took advantage of Kerrie Mengersen visiting Paris to write a common piece on the future of the refereeing system and on our proposals to improve it from within. Rather than tearing the whole thing down. In particular, one idea is to make writing referees’ reports part of the academic vitas, by turning them into discussions of published papers. Another one is to achieve some training of referees, by setting refereeing codes and more formalised steps. Yet another one is to federate reports rather than repeating the process one journal at a time for the unlucky ones… The resulting paper has now appeared on arXiv and has just been submitted (I am rather uncertain about the publication chances of this paper, given it is an opinion column, rather than a research paper…! It has already been rejected once, twice, three five times!)

the modern internet of things

Posted in University life with tags , on May 20, 2012 by xi'an

Here is an hillarious email I got this morning about a journal called the Modern Internet of Things (sic):

Dear Pro. , Considering your research in related areas, we cordially
invite you to submit a paper to Modern Internet of Things 
(MIOT). The Journal of Modern Internet of Things (MIOT) is 
published in English, andis a peer reviewed free-access 
journal which provides rapid publications and a forum for 
researchers, research results, and knowledge on Internet of 
Things. It serves the objective of international academic 
exchange. 

On the journal webpage, I noticed the following

Papers to be submitted to MIOT are required at least 6 pages after formatting according to the template on this website.

which is quite unusual a request since journals prefer to cull long papers!