Archive for slideshare
Bayesian privacies [slides]
Posted in Books, Statistics, Travel, University life with tags adversarial privacy, Bayesian privacy, differential privacy, inference, loss function, multi-agent decision theory, optimal decision, persuasive privacy, seminar, slides, slideshare, summary statistics, Università degli studi di Padova, utility on April 4, 2026 by xi'an
SEINE AI
Posted in pictures, Statistics, University life with tags #ERCSyG, adversarial learning, agent-based models, bandits, Bayesian learning, Bradley–Terry–Luce model, ChatGPT, hallucinations, Information and Communication Technology, INRIA, John Nash, Jouy-en-Josas, LLM, München, multi-agent decision theory, Nash equilibrium, Paris, Queen Mary University of London, reinforcement learning, Seine, slideshare, workshop, ye Norse farce on March 23, 2026 by xi'an
Ten days ago I took part in the SEINE AI 2026 workshop in Jouy-en-Josas, near Paris (homestead of HEC), organised by the Huawei Paris Research Center.. In which I was invited to speak, even though I felt sort of an outlier given the deeply machine-learning, entreprenarial orientation of the meeting, with its theme being Building the Agentic Future of ICT, given that I chose to present our most recent Bayesian adversarial privacy paper. Hence, I stood within a game-theoretic, Bayesian, formal landscape, presumably loosing most of the audience and keeping them away from their lunch!
Other speakers included Simon Lucas from Queen Mary London on Simulation-based AI, which I had trouble distinguishing from building a statistical model by goodness of fit (and using bandits used for update), while focussing on competing on some computer game challenges. And Volker Tresp from LMU München on a tensor brain model that he opposes to a Bayesian brain (with a related paper entitled Bayes or Heisenberg: Who(se) rules? which we discussed in general terms over lunch, namely Bayesian learning vs. quantum updating. And Michal Valko from INRIA Paris (and other companies), who went full blast against the Bradley-Terry model!, with a title of Nash and Nemirovski walk into a bar! With a half-time technique approximating Nash equilibria that reminded me of leapfrog. Much entertaining talk that further provided a game-theoretic transition to mine’s.
As an aside, I played yesterday with ChatGPT composing my talk slides out of our arXiv document and it proved a disaster, with hallucinations of results and concepts not in the paper and a complete mess of handling graphs, first creating generic, fake, unrelated pictures, then inserting actual graphs haphazardly throughout the slides. The sorry result I obviously did not use as the workshop did not seem the ideal place for this sort of prank! The actual version only recycles a few of its summarising slides. (With ye Norse farce proper colour choice!)
astrostat webinar [IAU-IAA]
Posted in pictures, Statistics, University life with tags astroinformatics, astrostatistics, G. Dou, IAA, IAU, International Astronomical Union, International Astrostatistics Association, ISI, mixture analysis, mixtures of distributions, seminar, slideshare, unknown number of components, webinar, Zoom on June 14, 2023 by xi'an
Yesterday, I gavea talk on inferring the number of components in a mixture at the international online IAU-IAA Astrostats and Astroinfo seminar. Which generated (uniformly) interesting and relevant questions for astronomical challenges. As pointed out by my Cornell friend Tom Loredo, it is unfortunately clashing with the ISI quadrenial Statistical Challenges in Modern Astronomy meeting help at Penn State.
diffusions, sampling, and transport
Posted in Books, pictures, Statistics, Travel, University life with tags anime, annealed importance sampling, Biometrika, deconvolution, diffusions, Flatiron Institute, flight mode, Hyvärinen score, JFK, Madison Square Garden, optimal transport, simulated annealing, slideshare, Stein's method on November 21, 2022 by xi'an
The third and final day of the workshop was shortened for me as I had to catch an early flight back to Paris (and as I got overly conservative in my estimation for returning to JFK, catching a train with no delay at Penn Station and thus finding myself with two hours free before boarding, hence reviewing remaining Biometrika submission at the airport while waiting). As a result I missed the afternoon talks.
The morning was mostly about using scores for simulation (a topic of which I was mostly unaware), with Yang Song giving the introductory lecture on creating better [cf pix left] generative models via the score function, with a massive production of his on the topic (but too many image simulations of dogs, cats, and celebrities!). Estimating directly the score is feasible via Fisher divergence or score matching à la Hyvärinen (with a return of Stein’s unbiased estimator of the risk!). And relying on estimated scores to simulate / generate by Langevin dynamics or other MCMC methods that do not require density evaluations. Due to poor performances in low density / learning regions a fix is randomization / tempering but the resolution (as exposed) sounded clumsy. (And made me wonder at using some more advanced form of deconvolution since the randomization pattern is controlled.) The talk showed some impressive text to image simulations used by an animation studio!
And then my friend Arnaud Doucet continued on the same theme, motivating by estimating normalising constant through annealed importance sampling [Yuling’s meta-perspective comes back to mind in that the geometric mixture is not the only choice, but with which objective]. In AIS, as in a series of Arnaud’s works, like the 2006 SMC Read Paper with Pierre Del Moral and Ajay Jasra, the importance (!) of some auxiliary backward kernels goes beyond theoretical arguments, with the ideally sequence being provided by a Langevin diffusion. Hence involving a score, learned as in the previous talk. Arnaud reformulated this issue as creating a transportation map and its reverse, which is leading to their recent Schrödinger bridge generative model. Which [imho] both brings a unification perspective to his work and an efficient way to bridge prior to posterior in AIS. A most profitable morn for me!
Overall, this was an exhilarating workshop, full of discoveries for me and providing me with the opportunity to meet and exchange with mostly people I had not met before. Thanks to Bob Carpenter and Michael Albergo for organising and running the workshop!
