Archive for Uber

me no savi [travel madness]

Posted in Statistics with tags , , , , , , , , on June 1, 2022 by xi'an

Today, I left home in the wee hours, after watering my tomatoes!, quite excited to join the Safe, Anytime-Valid Inference (SAVI) workshop in Eindhoven, which was taking place after two years of postponement. I alas did not check the state of the train traffic beforehand and when I reached the train station I found that part of the line to De Gaulle airport was closed, due to some control cables being stolen last night. Things quickly deteriorated as the train management in Gare du Nord was pretty inefficient, meaning that the trains would stop for five minutes at each station, and that there was no rail alternative to reach Roissy. The taxi stand was a complete mess, with no queue whatsoever, and the Parisian taxis kept true to their reputation, by refusing to take people to the airport, asking for outrageous prices (60 euros per passenger), and stopping anywhere. I almost managed to get one but he refused to take me on top of the Swede family I had directed to this stand from the RER train, and this was simply my last opportunity. Über taxis were invisible and I soon realised I could not catch my flight. Later flights were outrageously expensive and there was not train seat whatsoever till the day after, so I gave up and returned home from this trip to nowhere…

Bill’s 80th!!!

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , , , , , on April 17, 2022 by xi'an

“It was the best of times,
it was the worst of times”
[Dickens’ Tale of Two Cities (which plays a role in my friendship with Bill!)]

My flight to NYC last week was uneventful and rather fast and I worked rather well, even though the seat in front of me was inclined to the max for the entire flight! (Still got glimpses of Aline and of Deepwater Horizon from my neighbours.) Taking a very early flight from Paris was great making a full day once in NYC,  but “forcing” me to take a taxi, which almost ended up in disaster since the Über driver did not show up. At all. And never replied to my message. Fortunately trains were running, I was also running despite the broken rib, and I arrived at the airport some time before access was closed, grateful for the low activity that day. I also had another bit of a worrying moment at the US border control in JFK as I ended up in a back-office of the Border Police after the machine could not catch my fingerprints. And another stop at the luggage control as my lack of luggage sounded suspicious!The conference was delightful in celebrating Bill’s carreer and kindness (tinted with the most gentle irony!). Among stories told at the banquet, I was surprised to learn of Bill’s jazz career side, as I had never heard him play the piano or the clarinet! Even though we had chatted about music and literature on many occasions. Since our meeting in 1989… The (scientific side of the) conference included many talks around shrinkage, from loss estimation to predictive estimation, reminding me of the roaring 70’s and 80’s [James-Stein wise]. And demonstrating the impact of Bill’s wor throughout this era (incl. on my own PhD thesis). I started wondering at the (Bayesian) use of the loss estimate, though, as I set myself facing two point estimators attached with two estimators of their loss: it did not seem a particularly good idea to systematically pick the one with the smallest estimate (and Jim Berger confirmed this feeling on a later discussion). Among the talks on less familiar topics (of mine), I discovered work of Genevera Allen‘s on inferring massive network for neuron connections under sparse information. And of Emma Jingfei Zhang, equally centred on network inference, with applications to brain connectivity.

In a somewhat remote connection with Bill’s work (and our joint and hilarious assessment of Pitman closeness), I presented part of our joint and current work with Adrien Hairault and Judith Rousseau on inferring the number of components in a mixture by Bayes factors when the alternative is an infinite mixture (i.e., a Dirichlet process mixture). Of which Ruobin Gong gave a terrific discussion. (With a connection to her current work on Sense and Sensitivity.)

I was most sorry to miss Larry Wasserman’s and Rob Strawderman’s talk to rush back to the airport, the more because I am sure Larry’s talk would have brought a new light on causality (possibly equating it with tequila and mixtures!). The flight back was uneventfull, the plane rather empty and I slept most of the time. Overall,  it was most wonderful to re-connect with so many friends. Most of whom I had not seen for ages, even before the pandemic. And to meet new friends. (Nothing original in the reported feeling, just telling that the break in conferences and workshops was primarily a hatchet job on social relations and friendships.)

JSM 2015 [day #1]

Posted in Books, R, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , on August 10, 2015 by xi'an

ferryThis afternoon, at JSM 2015, in Seattle, we had the Bayesian Computation I and II sessions that Omiros Papaspiliopoulos and myself put together (sponsored by IMS and ISBA). Despite this being Sunday and hence having some of the participants still arriving, the sessions went on well in terms of audience. Thanks to Mark Girolami’s strict presidency, we were so much on time in Bayesian Computation I that we had 20mn left for a floor discussion that turned into a speakers’ discussion! All talks were of obvious interest for MCMCists, but Ryan Adams’ presentation on firefly Monte Carlo got me thinking for most of the afternoon on different ways of exploiting the existence of a bound on the terms composing the target. With little to show by the end of the afternoon! On the mundane side, I was sorry to miss Pierre Jacob, who was still in France due to difficulties in obtaining a working visa for Harvard (!), and surprised to see Dawn Woodard wearing a Uber tee-shirt, until she told us she was now working at Uber! Which a posteriori makes sense, given her work on traffic predictions!

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