The running shoe company Hoka (One One) is known *among runners at least) for its oversized soles that allow more cushion than competitors. (It was created in Annecy, French Alps, for local trailers, before being bought by an American group. The name of the brand means flying on Earth in Maori.) I had never tried any of their shoes, primarily due to the cost of the fastest ones, but in the days after Marseille-Cassis, I saw an add mentioning a free return after a 30 day trial and thus decided on testing a (pricey) competition model, the Cielo X1. Advertised as the fastest in their collection (with no mention made of any car brand!)I received the package a few days prior to my Boulogne half-marathon.
The shoe is highly unusual (for me), in that its soles are far from flat and make walking with then unpleasant. (When I travelled to Boulogne, I had to jog to keep my [detailed] balance!) The design is intended for (aggressive) forefoot attack, followed by a bounce from the talon created by a massive carbon plate. The upper part is also original, with a light but tight slipper that stabilises the foot inside the shoe. When I first tried them (the day they arrived), I was most puzzled and did a first short 8km run to check I could at all run with them. And realised that even without trying, I was running at a higher pace, especially downhill. The next day, I pushed a bit harder on my 10km route and noticed the same improvement, hence got confident that I should use them for the Boulogne half-marathon. Post-race, I remain convinced them helped in keeping a below 4mn pace, if not enormously (with a 90 second gain compared with 2023), as my muscles started protesting about half-way. But the end of the race was not as dreadful as usual, possibly thanks to the shoes, possibly thanks to a higher training volume. Will I keep the shoes? At that price, I am afraid not! But this was a great experience (and I will keep looking for sales in the coming months).
Archive for trail running
trialing a Porsch[o]e
Posted in Mountains, pictures, Running, Travel with tags Annecy, Boulogne-Billancourt, carbon plate, competition, design, detailed balance, foam protection, France, French Alps, Hoka One One, Maori language, running shoes, semi-marathon, trail running, ultramarathon on December 5, 2024 by xi'an6th Workshop on Sequential Monte Carlo Methods
Posted in Mountains, pictures, Statistics, Travel, University life with tags #ERCSyG, Arthur's Seat, auxiliary particle filter, Bayes Centre, Da Vinci Code, Edinburgh, Gaussian processes, generative models, gradient algorithm, Hamiltonian, ICMS, MALA, maximal coupling, multilevel Monte Carlo, neural network, Ocean, ODE, particle filter, Pentland Hills, public transportation, robots, Rosslyn Chapel, Scotland, SMC, SMC 2024, snippet, trail running on May 16, 2024 by xi'an
Very glad to be back to an SMC workshop as it has been nine years since my attending SMC 2015 in Malakoff! The more for the workshop taking place in Edinburgh and at the Bayes Centre. It is one of these places where I feel somewhat returning to familiar grounds with accumulated memories. Like my last visit there when I had a tea with Mike Titterington…
The overall pace of the workshop was quite nice, with long breaks for informal discussions (and time for ‘oggin’!) and interesting poster late afternoons, helped by the small number of them at each instance, incl. one on reversible jump HMC. Here are a few scribbled entries about some talks along the first two days.
After my opening talk (!), Joaquín Míguez talked about the impact of a sequential (Euler-Marayama) discretisation scheme for stochastic differential equations on Bayesian filtering with control of the approximation effect. Axel Finke (in a joint work with Adrien Corenflos, now an ERC Ocean postdoc in Warwick) built a sequence of particle filter algorithms targeting good performances (high expected jumping distance) against both large dimensions and high time horizon, exploiting gradient shift MALA-like, as well as prior impact, with the conclusion that their jack-of-all-trades solutions, Particle-MALA and Particle-mGRAD, enjoyed this resistance in nearly normal models. Interesting reminder of the auxiliary particle trick and good insights on using the smoothing target, even when accounting for the computing time, but too many versions for a single talk without checking against the preprint.
The SMC sampler-like algorithm involves propagating N “seed” particles z(i), with a mutation mechanism consisting of the generation of N integrator snippets 𝗓:=(z,ψ(z),ψ²(z),…) started at every seed particle z(i), resulting in N×(T+1) particles which are then whittled down to a set of N seed particles using a standard resampling scheme. Andrieu et al., 2024
Christophe Andrieu talked about Monte Carlo sampling with integrator snippets, starting with recycling solutions for the leapfrog integrator HMC and unfolding Hamiltonians for moving more easily. With snippets representing discretised paths along the level sets being used as particles, picking zero, one, or more particles along each path, since importance weights are connection with multinomial HMC
This relatively small algorithmic modification of the conditional particle filter, which we call the conditional backward sampling particle filter has a dramatically improved performance over the conditional particle filter. Karjalainen et al., 2024
Anthony Lee looked at mixing times for backward sampling SMC (CBPF/ancestor sampling) cf Lee et al. (2020), where the backward step consists in computing the weight of a randomly drawn backward or ancestral history. Improving on earlier results to reach mixing time O(log T) and complexity O(T log T) (with T the time horizon). Thanks to maximal coupling and boundedness assumptions on the prior and likelihood functions.
Neil Chada presented a work on Bayesian multilevel Monte Carlo on deep networks. À la Giles, with a telescoping identity. Always puzzling to envision a prior on all parameters of a neural network. Achieving a computational cost inverse to the order of the MSE, at best. With a useful reminder that pushing the size of the NN to infinity results in a (poor) Gaussian process prior (Sell et al., 2023).
On my first evening, I stopped with a friend in my favourite Blonde [restaurant], as in almost every other visit to Edinburgh, enjoyable as always, but I also found the huge offer of Asian minimarkets in the area too tempting to resist, between Indian, Korean, and Chinese products. (Although with a disappointing hojicha!). As I could not reach any new Munro by train or bus within a reasonable time range I resorted to the nearer Pentland Hills, with a stop by Rosslyn Chapel (mostly of Da Vinci Code fame!, if classic enough). And some delays in finding a bus getting there (misled by google map!) and a trail (misled by my poor map reading skills) up the actual hills. The mist did not help either.
sunrise boulevard, Aubrac [jatp]
Posted in Mountains, pictures, Running, Travel with tags Aubrac, Auvergne, Cévennes, jatp, morning run, Saint-Laurent d'Olt, sunrise, trail running, winter light on January 3, 2024 by xi'an
off to Martinique [#2]
Posted in Kids, Mountains, pictures, Running, Travel with tags Caribean sea, family, Fort-de-France, Martinique, medical thesis, Montagne Pelée, outremer, pitons, residency, thesis defence, trail running, volcano, West Indies on October 18, 2023 by xi'an
Ring of Steall 2022
Posted in Statistics with tags Glen Nevis, Glencoe, Kinlochleven, Mamores, munroes, Ring of Steall, Salomon, Scotland, Skyline Scotland, trail running on September 18, 2022 by xi'an
