AI for good

Last week, I had a quick chat in front of the Luxembourg gardens with Julien Cornebise and he told me about the AI for Good Foundation with whom he was going to work through Element AI, after doing volunteer work with Amnesty International. Great!

champagne, not Guinness??? [jatp]

MUDAM

As our son is doing an internship in Luxembourg City this semester, we visited him last weekend and took the opportunity to visit the Museum of Modern Art (or MUDAM) there. The building itself is quite impressive, inserted in the walls of the 18th Century Fort Thüngen designed by Vauban, with a very luminous and airy building designed by Ming Pei. The main exhibit at the MUDAM is a coverage of the work on Su-Mei Tse, an artist from Luxembourg I did not know but whom vision I find both original and highly impressive, playing on scales and space, from atoms to planets… With connections to Monet’s nympheas. And an almost raw rendering of rock forms that I appreciate most particularly!

The bottom floor also contains an extensive display of the political drawings of Ad Reinhardt, who is more (?) famous for his black-on-black series…

splitting a field by annealing

A recent riddle [from The Riddle] that I pondered about during a [long!] drive to Luxembourg last weekend was about splitting a square field into three lots of identical surface for a minimal length of separating wire… While this led me to conclude that the best solution was a T like separation, I ran a simulated annealing R code on my train trip to AutransValence, seemingly in agreement with this conclusion.I discretised the square into n² units and explored configurations by switching two units with different colours, according to a simulated annealing pattern (although unable to impose connectivity on the three regions!):

partz=matrix(1,n,n)
partz[,1:(n/3)]=2;partz[((n/2)+1):n,((n/3)+1):n]=3
#counting adjacent units of same colour 
nood=hood=matrix(4,n,n)
for (v in 1:n2) hood[v]=bourz(v,partz)
minz=el=sum(4-hood)
for (t in 1:T){
  colz=sample(1:3,2) #picks colours
  a=sample((1:n2)[(partz==colz[1])&(hood<4)],1)
  b=sample((1:n2)[(partz==colz[2])&(hood<4)],1) 
  partt=partz;partt[b]=colz[1];partt[a]=colz[2] 
#collection of squares impacted by switch 
  nood=hood 
  voiz=unique(c(a,a-1,a+1,a+n,a-n,b-1,b,b+1,b+n,b-n)) 
  voiz=voiz[(voiz>0)&(voiz<n2)] 
  for (v in voiz) nood[v]=bourz(v,partt) 
  if (nood[a]*nood[b]>0){
    difz=sum(nood)-sum(hood)
    if (log(runif(1))<difz^3/(n^3)*(1+log(10*rep*t)^3)){
      el=el-difz;partz=partt;hood=nood     
      if (el<minz){ minz=el;cool=partz}
  }}}

(where bourz computes the number of neighbours), which produces completely random patterns at high temperatures (low t) and which returns to the T configuration (more or less):if not always, as shown below:Once the (a?) solution was posted on The Riddler, it appeared that one triangular (Y) version proved better than the T one [if not started from corners], with a gain of 3% and that a curved separation was even better with an extra gain less than 1% [solution that I find quite surprising as straight lines should improve upon curved ones…]

life and death along the RER B, minus approximations

While cooking for a late Sunday lunch today [sweet-potatoes röstis], I was listening as usual to the French Public Radio (France Inter) and at some point heard the short [10mn] Périphéries that gives every weekend an insight on the suburbs [on the “other side’ of the Parisian Périphérique boulevard]. The idea proposed by a geographer from Montpellier, Emmanuel Vigneron, was to point out the health inequalities between the wealthy 5th arrondissement of Paris and the not-so-far-away suburbs, by following the RER B train line from Luxembourg to La Plaine-Stade de France…

The disparities between the heart of Paris and some suburbs are numerous and massive, actually the more one gets away from the lifeline represented by the RER A and RER B train lines, so far from me the idea of negating this opposition, but the presentation made during those 10 minutes of Périphéries was quite approximative in statistical terms. For instance, the mortality rate in La Plaine is 30% higher than the mortality rate in Luxembourg and this was translated into the chances for a given individual from La Plaine to die in the coming year are 30% higher than if he [or she] lives in Luxembourg. Then a few minutes later the chances for a given individual from Luxembourg to die are 30% lower than he [or she] lives in La Plaine…. Reading from the above map, it appears that the reference is the mortality rate for the Greater Paris. (Those are 2010 figures.) This opposition that Vigneron attributes to a different access to health facilities, like the number of medical general practitioners per inhabitant, does not account for the huge socio-demographic differences between both places, for instance the much younger and maybe larger population in suburbs like La Plaine. And for other confounding factors: see, e.g., the equally large difference between the neighbouring stations of Luxembourg and Saint-Michel. There is no socio-demographic difference and the accessibility of health services is about the same. Or the similar opposition between the southern suburban stops of Bagneux and [my local] Bourg-la-Reine, with the same access to health services… Or yet again the massive decrease in the Yvette valley near Orsay. The analysis is thus statistically poor and somewhat ideologically biased in that I am unsure the data discussed during this radio show tells us much more than the sad fact that suburbs with less favoured populations show a higher mortality rate.

Au Luxembourg

In a “crazy travelling week” (dixit my daughter), I gave a talk at an IYS 2013 conference organised by Stephen Senn (formerly at Glasgow) and colleagues in the city of Luxembourg, Grand Duché du Luxembourg. I enjoyed very much the morning train trip there as it was a misty morning, with the sun rising over the frosted-white countryside. (I cannot say much about the city of Luxembourg itself though as I only walked the kilometre from the station to the conference hotel and the same way back. There was a huge gap on the plateau due to a river in the middle, which would have been a nice place to run, I presume…)

One of the few talks I attended there was about an econometric model with instrumental variables. In general, and this dates back to my student’s years at ENSAE, I do not get the motivation for the distinction between endogenous and exogenous in econometrics models. Especially in non-parametric models as, if we do not want to make parametric assumptions, we have difficulties in making instead correlation hypotheses… My bent would be to parametrise everything under the suspicion of this everything being correlated with everything. The instrumental variables econometricians seem so fond of appear to me like magical beings, since we have to know they are instrumental. And because they seem to allow to always come back to a linear setting, by eliminating the non-linear parts. Sounds like a “more for less” free-lunch deal. (Any pointer would be appreciated.) The speaker there actually acknowledged (verbatim) that they are indeed magical and that they cannot be justified by mathematics or statistics. A voodoo part of econometrics then?!

A second talk that left me perplexed was about a generalised finite mixture model. The model sounded like a mixture along time of individuals, ie a sort of clustering of longitudinal data. It looked like it should be easier to estimate than usual mixtures of regressions because an individual contributed to the same regression line for all the times when it was observed. The talk was uninspiring as it missed connections to EM and to Bayesian solutions, focussing instead on a gradient method that sounded inappropriate for a multimodal likelihood. (Funny enough, the choice in the number of regressions was done by BIC.)

travellin’ week ahead

Next 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!