Archive for Canada

an oldie but a goldie [jatp]

Posted in Mountains, pictures, Travel, University life with tags , , , , , , , , on March 19, 2020 by xi'an

Colin Blyth (1922-2019)

Posted in Books, pictures, Statistics, University life with tags , , , , , , , , , , , , , , , , , on March 19, 2020 by xi'an

While reading the IMS Bulletin (of March 2020), I found out that Canadian statistician Colin Blyth had died last summer. While we had never met in person, I remember his very distinctive and elegant handwriting in a few letters he sent me, including the above I have kept (along with an handwritten letter from Lucien Le Cam!). It contains suggestions about revising our Is Pitman nearness a reasonable criterion?, written with Gene Hwang and William Strawderman and which took three years to publish as it was deemed somewhat controversial. It actually appeared in JASA with discussions from Malay Ghosh, John Keating and Pranab K Sen, Shyamal Das Peddada, C. R. Rao, George Casella and Martin T. Wells, and Colin R. Blyth (with a much stronger wording than in the above letter!, like “What can be said but “It isn’t I, it’s you that are crazy?”). While I had used some of his admissibility results, including the admissibility of the Normal sample average in dimension one, e.g. in my book, I had not realised at the time that Blyth was (a) the first student of Erich Lehmann (b) the originator of [the name] Simpson’s paradox, (c) the scribe for Lehmann’s notes that would eventually lead to Testing Statistical Hypotheses and Theory of Point Estimation, later revised with George Casella. And (d) a keen bagpipe player and scholar.

Panch at the helm!

Posted in pictures, Travel, University life with tags , , , , , , , , , , , , on January 8, 2020 by xi'an

Reading somewhat by chance a Nature article on the new Director of the National Science Foundation (NSF) nominated by Trump (and yet to be confirmed by the Senate), I found that his name Sethuraman Panchanathan was the name of a friend of my wife 30⁺ years ago when they were both graduate students in image processing at the University of Ottawa, Department of Electrical Engineering… And looking further into the matter, I realised that this was indeed the very friend we knew from that time, with whom w shared laughs, dinners, and a few day trips together around Ottawa! While this is not the ultimate surprise, given that science administration is usually run by scientists, taken from a population pool that is not that large, as exemplified by earlier cases at the national or European level where I had some acquaintance with a then senior officer, it is nonetheless striking (and fun) to hear of a friend moving to a high visibility position after such a long gap. (When comparing NSF and ERC, the European Research Council, with French mathematician Jean-Pierre Bourguignon as current director also appearing in a recent Nature article, I was surprised to see that the ERC budget was more than twice the NSF budget.) Well, good luck to him for sailing these highly political waters!

start of 2020

Posted in Kids, Mountains, pictures, Travel with tags , , , , , on January 1, 2020 by xi'an

tea tasting at Van Cha

Posted in Kids, pictures, Travel with tags , , , , , , , , , , , , , on December 26, 2019 by xi'an

This recent trip to Vancouver gave me the opportunity of enjoying a Chinese tea tasting experience. On my last visit to the city, I had noticed a small tea shop very near the convention centre but could not find the time to stop there. This round I took advantage of the AABI lunch break to get back to the shop, which was open (on a Sunday), and sat for a ripe Pu-Ehr tasting. A fatal if minor mistake in ordering, namely that this was Pu-Ehr withing a dried yuzu shell, which gave the tea a mixed taste of fruit and tea, as least for the first brews. And remaining very far from the very earthy tastes I was expecting. (But it reminded me of a tangerine based Pu-Ehr Yulia gave me last time we went to Banff. And I missed an ice climbing opportunity!)
This was nonetheless a very pleasant tasting experience, with the tea hostess brewing one tiny tea pot after another, including a first one to wet and clean the tea, with very short infusion times, and tea rounds keeping their strong flavour even after several passes. In a very quiet atmosphere altogether, with a well-used piece of wood (as shown on top) in lieu of a sink to get rid of the water used to warm and clean pots and mugs (and a clay frog which role remained mysterious throughout!).
At some point in the degustation, another customer came in, obviously from a quite different league as he was carrying his own tea pancake, from which the hostess extracted a few grams and processed most carefully. This must have been an exceptional tea as she was rewarded by a small cup of the first brew, which she seemed to appreciate a lot (albeit in Chinese so I could not say).
As I was about to leave, having spent more time than expected and drank five brews of my tea, plus extra cups of a delicate Oolong, hence missing a talk by Matt Hoffman to which I was looking forward!, I discussed for a little while with this connoisseur, who told me of the importance of using porous clay pots and not mix them for different teas. Incidentally he was also quite dismissive of Japanese teas, (iron) teapots, and tea ceremony, which I found in petto a rather amusing attitude (if expected from some aficionados).

no dichotomy between efficiency and interpretability

Posted in Books, Statistics, Travel, University life with tags , , , , , , , , , , , , on December 18, 2019 by xi'an

“…there are actually a lot of applications where people do not try to construct an interpretable model, because they might believe that for a complex data set, an interpretable model could not possibly be as accurate as a black box. Or perhaps they want to preserve the model as proprietary.”

One article I found quite interesting in the second issue of HDSR is “Why are we using black box models in AI when we don’t need to? A lesson from an explainable AI competition” by Cynthia Rudin and Joanna Radin, which describes the setting of a NeurIPS competition last year, the Explainable Machine Learning Challenge, of which I was blissfully unaware. The goal was to construct an operational black box predictor fpr credit scoring and turn it into something interpretable. The authors explain how they built instead a white box predictor (my terms!), namely a linear model, which could not be improved more than marginally by a black box algorithm. (It appears from the references that these authors have a record of analysing black-box models in various setting and demonstrating that they do not always bring more efficiency than interpretable versions.) While this is but one example and even though the authors did not win the challenge (I am unclear why as I did not check the background story, writing on the plane to pre-NeuriPS 2019).

I find this column quite refreshing and worth disseminating, as it challenges the current creed that intractable functions with hundreds of parameters will always do better, if only because they are calibrated within the box and have eventually difficulties to fight over-fitting within (and hence under-fitting outside). This is also a difficulty with common statistical models, but having the ability to construct error evaluations that show how quickly the prediction efficiency deteriorates may prove the more structured and more sparsely parameterised models the winner (of real world competitions).

midnight run

Posted in Running, Travel with tags , , , , , , , , on December 8, 2019 by xi'an