Archive for the Running Category
Visiting relatives for the New Year break, I had two wonderful opportunities to sample chef’s restaurants in Normandy. One was Ivan Vautier’s IV in Caen, who had recently lost one Michelin star out of two, but seems to deserve two from the quality of the food and service we received for lunch. For instance, this poached egg… (Definitely above the X I tested twice in 2015.) Plus a great touch of connecting with the local producers, whose pictures were posted in the entrance to the restaurant. The second restaurant was Pavillon de Gouffern, located in a forest near Argentan (and almost on the path of my traditional half-marathon). Worth recommending if only for the setting, in a former hunting lodge, superbly quiet with great views. Plus a well-made scampi risotto, ultimately creamy. And a wide collection of local pear-ciders.
After the day trip to Montréal, a quick stop in Paris, and another one in London, I thought back on the probabilistic integration workshop of last week. First, I had a very good time discussing with people there, with no (apparent) adverse reaction to my talk on “estimating constants”. Second, I finally realised what Mark Berliner meant by saying that he was a Bayesian if not a statistician, in a discussion we had in the early 1990’s, in Cornell. Third, I became [moderately] more open to the highly structured spaces used in the approaches discussed by François-Xavier Briol, Arthur Gretton, Roman Garnett, and Francis Bach. The (RKHS) functional assumptions made in those approaches are allowing for higher and more precise convergence rates, with the question being what happens when the assumptions do not hold. A comment similar to the impact of a Gaussian process as the prior on the integrand in Bayesian quadrature.
François-Xavier presented the recently arXived probabilistic integration that Andrew discussed a week ago. (While I obviously have no relevant remark to make about the maths in this paper, I wonder at the difficulty and cost in sequentially selecting the states behind the quadrature. Which presumably is covered in the earlier Frank-Wolfe paper by the same team.) Another discussion with Arthur clarified a wee bit how RKHS can be perceived in practice, with a lingering question on the size of RKHS within the entire space of functions and more importantly the significant impact of the kernel representation on the resulting approximations. Anyway, those are exciting times, when considering that different branches of numerics and probability and statistics come together to improve upon existing techniques and I am once again glad I could took part in this workshop (although sorry I had to miss the ABC workshop that took place in parallel!)