Archive for Seine

semi de Boulogne [1:29:33, 1243/8134, M5M 6/206, 8⁰+rain]

Posted in pictures, Running with tags , , , , , , , on December 1, 2022 by xi'an

First time back to the Boulogne half-marathon since 2008! With clearly a much degraded time, albeit better than the previous race in Argentan. The route has changed, with a longer part in the Bois de Boulogne, sharing the road with the hordes of Sunday cyclists that pile up loops at high speed. But still a very fast one (with a record at 1:00:11 in 2013). The number has alas considerably increased since my last visit, with 9800 registrations, which makes running in the first kilometers a challenge with hidden sidewalks, parked cars and moppets, &tc. And a permanent difficulty in passing other runners, especially on a rainy day. (The only good side was being protected from headwinds.) Once on the road by the Seine River, I managed to pass a large group conglomerated around a (1:30) pace setter and moved at my own speed, till Km16 when I started to tire and realise I was alas missing some volume of training (as running in NYC was only a slow-paced jogging). Hence wasting about a minute on the final four kilometers… (Jogging back after the race to my car, parked 3km away, proved rather painful!) As the 1:30 time was my upper limit, I am still reasonably fine with the result (and the 4’14” per km) and hope I can train harder for the next race.

17 octobre 1961 [memory of a massacre]

Posted in pictures with tags , , , , , , , , , , on October 17, 2021 by xi'an

`Paris is in anarchy’ [cycle woes]

Posted in Travel with tags , , , , , , , , , , on October 7, 2021 by xi'an

An overblown view of the cycling war in Paris, from New York! I read with amusement the report on how Xing a Parisian street is a matter of life or death, when anarclists go through red lights while shouting at pedestrians… Actually, the figures show that the number of accidents involving cyclists (as victims or culprits) has only gone up by 30% when the traffic has increased by 70%. And I could not find an online trace of a pedestrian killed by a cyclist over the past years. Based on my weekly 130 kilometer biking average, mostly to and from Paris Dauphine, I do not perceive a major tension between pedestrians and cyclists, maybe because I am not entering the centre of town (and give priority to pedestrians at both green and red lights). The danger in my experience comes rather from other cyclists’ unpredictable paths, (psychopath) mopeds that run on cycle paths, and cars turning right without checking for bicycles. But I concur with the point made in this article of a poor network of cycle paths, with too many discontinuities, bad surface, inexistent maintenance (esp. in winter months when wet leaves accumulate there and all year long for broken glass and metal parts), and the deadly pavés! Which are unpleasant for road bikes (ask the Paris-Roubaix runners!), slippery, esp. when frosted (speaking from experience), and damaging to tubes and ties. As it happens, I have had thee tube punctures over the three past weeks, two of which were due to running over a particularly uneven pavé or entering a cycle path with a very high step. (And a total of six since April. Making me reconsider using an heavier mountain bike instead. After switching unsuccessfully to anti-puncture road tyres…)

Tour de Paris [of pools]

Posted in Kids, pictures, Running, Travel with tags , , , , , , , on April 25, 2021 by xi'an

As I am prevented from running since the beginning of this year, due to a ligament injury caused by an excess of kilometers run since the beginning of the (first) lockdown, I have started swimming most days I can find a free window of time. And an open swimming pool! While Paris and most of the suburban cities near me have a decent offer of (cheap) public pools, it is often a challenge to find one open at a manageable time. Meaning for me mostly in the early morning. The lockdown has obviously reduced opening hours and introduced restricted access, requiring a medical certificate for indoor pools, and I have thus being recently visiting a rather extensive array of pools to fit such constraints, since both nearby pools, at home and at work, are rarely available. Last week, I biked to the most exotic so far, namely a pool made from a barge standing on the Seine River. It is alas not yet outdoor, but not yet crowded either (if small and rather hot). By comparison, the nearer and wider pool at Porte d’Orléans is surprisingly crowded at 7am (but pleasantly colder) and the historical pool on Butte aux Cailles also gets quickly crowded and is missing its outdoor pool (but is close to a fantastic bakery!). Even careful scheduling does not always work as I sometimes find an unexpected closed door, as two weeks ago when Butte aux Cailles had emptied overnight or a few days ago when Joséphine Baker had a disfunctioning pediluvium enough to bar entry. (The outdoor 50m pool in Villejuif I used to go to has just reopened to the general public and is not yet overcrowded, despite milder temperatures.)

double descent

Posted in Books, Statistics, University life with tags , , , , , , , , , , , on November 7, 2019 by xi'an

Last Friday, I [and a few hundred others!] went to the SMILE (Statistical Machine Learning in Paris) seminar where Francis Bach was giving a talk. (With a pleasant ride from Dauphine along the Seine river.) Fancis was talking about the double descent phenomenon observed in recent papers by Belkin & al. (2018, 2019), and Mei & Montanari (2019). (As the seminar room at INRIA was quite crowded and as I was sitting X-legged on the floor close to the screen, I took a few slides from below!) The phenomenon is that the usual U curve warning about over-fitting and reproduced in most statistics and machine-learning courses can under the right circumstances be followed by a second decrease in the testing error when the number of features goes beyond the number of observations. This is rather puzzling and counter-intuitive, so I briefkly checked the 2019 [8 pages] article by Belkin & al., who are studying two examples, including a standard “large p small n” Gaussian regression. where the authors state that

“However, as p grows beyond n, the test risk again decreases, provided that the model is fit using a suitable inductive bias (e.g., least norm solution). “

One explanation [I found after checking the paper] is that the variates (features) in the regression are selected at random rather than in an optimal sequential order. Double descent is missing with interpolating and deterministic estimators. Hence requiring on principle all candidate variates to be included to achieve minimal averaged error. The infinite spike is when the number p of variate is near the number n of observations. (The expectation accounts as well for the randomisation in T. Randomisation that remains an unclear feature in this framework…)

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