While the workshop schedule in Les Houches was rather tight and exhausting, I managed to squeeze in early morning runs as well as one (and only one) later morning ski session on the Kandahar run of Les Houches. Run that was quite nice due both to the quality of the snow and to the low occupancy, as French school vacations were not yet underway. Actually this Alpine week was my first week of steady running since Xmas, as my sciatica re-awoke on the very morning we were leaving for India, as I found out then during a 5am fast & furious run before heading to CDG Airport. It had been years since my sciatic nerve hurt that much and it took me up to my arrival in Chamonix to feel okay enough when running more than 4km at once. To compensate for the loss I turned through January to pool training most mornings but this proved more complicated, both timewise and locationwise, since very few nearby pools open at 7am at least once a week. And they are relatively nearby, meaning an extra 10km of extra biking at the very least each day. Henceforth a significant part of the morn having evaporated by the time I am heading to work. Still this daily training improved my swimming to some extent, mostly my endurance to get over 2km, as my speed only improved at most 10%! As I am preparing for another half-marathon at the end of March, I hope I can get back to the speed and volume reached the past Fall, tant pis for the swimming! (Unless I run to and from the pools.)
Archive for ERC Synergy Grant
[H]ouch[es]!
Posted in Running, Travel with tags #ERCSyG, Behaviours Invertebrates, Chamonix, Chamonix-Mont-Blanc, ERC Synergy Grant, half-marathon, indoor swimming, Kandahar, Les Houches, MRI, Ocean, road running, running injuries, sciatic nerve, sciatica, spine, swimming pool on February 16, 2025 by xi'anbused to Chamonix [jatp]
Posted in Statistics with tags Chamonix-Mont-Blanc, cross-country skiing, ERC Synergy Grant, French Alps, jatp, Les Houches, Ocean, Pays du Mont-Blanc, sunrise, Travel, winter light, workshop on February 6, 2025 by xi'an
more oceanographers in Les Houches
Posted in Books, Kids, Mountains, pictures, Running, Statistics, Travel, University life with tags #ERCSyG, Bayesian privacy, Chamonix, CHANCE, differential privacy, ERC, ERC Synergy Grant, fairness, French Alps, Les Houches, Ocean, summer school, uncertainty quantification, workshop on February 2, 2025 by xi'an
Our second internal research workshop on privacy, covered by our ERC Synergy project OCEAN is taking place in Les Houches, French Alps, this very week with 12 researchers gathering for further brain-storming on some of the themes at the core of the project, like algorithmic tools for multiple decision-making agents, along with Bayesian uncertainty quantification and Bayesian learning under constraints (scarcity, fairness, privacy). Due to the small size of the workshop, it will take place in the same local (and uncommon) hotel as last year. And where I had a genuine blackboard delivered (to be donated afterwards to École de Physique des Houches), as the place is not used to mathematicians discussing on and around a blackboard. Even though the schedule does not leave much time for skiing, I hope for a few opportunities, given that the ski cover is quite good this year!
sampling using adaptive regenerative processes [in print!]
Posted in pictures, Statistics, University life with tags #ERCSyG, academic journals, adaptive MCMC methods, adaptive Monte Carlo algorithm, Bernoulli, Bernoulli society, eadem mutata resurgo, ERC Synergy Grant, Markov process, Ocean, Project euclid, regeneration, University of Warwick on November 16, 2024 by xi'an
MCMC for Bayesian nonparametric mixture modeling under differential privacy
Posted in pictures, Statistics, Travel, University life with tags Bayesian conference, Bayesian inference, Benedictines, Cini Fundation, ERC Synergy Grant, flawed data, Fundazione Giorgio Cini, ISBA 2024, Italy, Ocean, privacy, San Giorgio Maggiore, satellite meetings, vaporetto, Venezia, Venice on July 21, 2024 by xi'an
At the ISBA-Cini workshop on Artificial intelligence, data sharing and regulation, a satellite of ISBA 2024 that was also an ERC Ocean workshop, located in the magnificent buildings of a former Benedictine Monastery (next to the Palladian church), Stéfano Favaro gave a presentation of the output of his ERC Consolidator Grant “Nonparametric Bayes and Empirical Bayes for Species Sampling Problem”, in which he discussed in particular the corpus of work they produced on Bayesian inference with flawed data. He mentioned in particular a recent paper with Mario Berah and Vinayak Rao on running MCMC for Bayesian non-parametric estimation on privatized (noisy) data.
“…if the original dataset Y is modelled as a realization of a BNP mixture model, then, after marginalizing out the Yi’s, the Zi’s again follow a nonparametric mixture model….”
“…our approach has the flavour of the pseudo-marginal MCMC approach (Andrieu and Roberts, 2009), with the latent Yi’s introduced back into the MCMC state as auxiliary variables to deal with intractable Metropolis-Hastings probabilities…”
“As mentioned in Ju et al. (2022), the efficiency of our algorithms are linked to the special structure of differential privacy…”
The paper starts from a privatized model where the data is perturbed to ensure (standard) differential privacy and only examines the convergence impact of the additional randomness layer on MCMC performances, depending on two versions… One re-simulating the hidden data given everything else and the other close to Neal’s (2000) for this specific hierarchical model. While more involved, the resulting MCMC samplers are not much different from the original ones since the privatization leads to replacing the initial distribution with a convolution, but the actual data still proceeds from an infinite mixture. In that respect, the paper does not engage in a discussion of privacy, like the impact of the BNP estimation, possible gains due to producing a BNP estimator, &tc. The only clear impact of the privacy assumptions is that the Metropolis-Hastings acceptance probability is lower bounded, but this was also noticed in Ju et al. (2022). It would have been nice to assess the impact of non-parametrics on further protecting the data if any!
