Archive for machine learning

Laplace’s Demon [coming home!]

Posted in Kids, Linux, pictures, Statistics, University life with tags , , , , , , , , , , , , , on May 11, 2020 by xi'an

A new online seminar is starting this week, called Laplace’s Demon [after too much immersion in His Dark Materials, lately, ather than Unix coding, I first wrote daemon!] and concerned with Bayesian Machine Learning at Scale. Run by Criteo in Paris (hence the Laplace filiation, I presume!). Here is the motivational blurb from their webpage

Machine learning is changing the world we live in at a break neck pace. From image recognition and generation, to the deployment of recommender systems, it seems to be breaking new ground constantly and influencing almost every aspect of our lives. In this seminar series we ask distinguished speakers to comment on what role Bayesian statistics and Bayesian machine learning have in this rapidly changing landscape. Do we need to optimally process information or borrow strength in the big data era? Are philosophical concepts such as coherence and the likelihood principle relevant when you are running a large scale recommender system? Are variational approximations, MCMC or EP appropriate in a production environment? Can I use the propensity score and call myself a Bayesian? How can I elicit a prior over a massive dataset? Is Bayes a reasonable theory of how to be perfect but a hopeless theory of how to be good? Do we need Bayes when we can just A/B test? What combinations of pragmatism and idealism can be used to deploy Bayesian machine learning in a large scale live system? We ask Bayesian believers, Bayesian pragmatists and Bayesian skeptics to comment on all of these subjects and more.

The seminar takes places on the second Wednesday of the month, at 5pm (GMT+2) starting ill-fatedly with myself on ABC-Gibbs this very Wednesday (13 May 2020), followed by Aki Vehtari, John Ormerod, Nicolas Chopin, François Caron, Pierre Latouche, Victor Elvira, Sara Filippi, and Chris Oates. (I think my very first webinar was a presentation at the Deutsche Bank, New York, I gave from CREST videoconference room from 8pm till midnight after my trip was cancelled when the Twin Towers got destroyed, on 07 September 2001…)

assistant/associate professor position in statistics/machine-learning at ENSAE

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , on March 10, 2020 by xi'an

ENSAE (my Alma Mater) is opening a new position for next semester in statistics or/and machine-learning. At the Assistant Professor level, the position is for an initial three-year term, renewable for another three years, before the tenure evaluation. The school is located on the Université Paris-Saclay campus, only teaches at the Master and PhD levels, and the deadline for application is 31 March 2020. Details and contacts on the call page.

Julyan’s talk on priors in Bayesian neural networks [cancelled!]

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , , on March 5, 2020 by xi'an

Next Friday, 13 March at 1:30p.m., Julyan Arbel, researcher at Inria Grenoble will give a All about that Bayes talk at CMLA, ENS Paris-Saclay (building D’Alembert, room Condorcet, Cachan, RER stop Bagneux) on

Understanding Priors in Bayesian Neural Networks at the Unit Level

We investigate deep Bayesian neural networks with Gaussian weight priors and a class of ReLU-like nonlinearities. Bayesian neural networks with Gaussian priors are well known to induce an L², “weight decay”, regularization. Our results characterize a more intricate regularization effect at the level of the unit activations. Our main result establishes that the induced prior distribution on the units before and after activation becomes increasingly heavy-tailed with the depth of the layer. We show that first layer units are Gaussian, second layer units are sub-exponential, and units in deeper layers are characterized by sub-Weibull distributions. Our results provide new theoretical insight on deep Bayesian neural networks, which we corroborate with simulation experiments.

 

Gabriel’s talk at Warwick on optimal transport

Posted in Statistics with tags , , , , , , on March 4, 2020 by xi'an

Irène Waldspurger, CNRS bronze medal

Posted in Statistics with tags , , , , , , on February 14, 2020 by xi'an

My colleague at Paris Dauphine, Irène Waldspurger, got one of the prestigious CNRS bronze medals this year. Irène is working on inverse problems and machine learning, with applications to sensing and imaging. Congrats!