Connectionists: Bayesian Machine Learning at Scale Webinar Starting Wed 13 May

[david rohde]

We are very pleased to announce: Laplace's Demon, Bayesian Machine Learning
at Scale (BMLS), a seminar series about practical Bayesian methods in
academia and industry.
https://sites.google.com/view/laplacesdemon/home

The first session of BMLS will be on the 13th of may at 15.00 UTC and will
be given by Christian Robert of Université Paris-Dauphine.  The second
session will be on the 10 June and given by Aki Vehtari of Aalto
University.  The third session will be on 1 July by John Ormerod of The
University of Sydney.

We will announce details of other upcoming speakers as they become
available, including:
Nicolas Chopin, François Caron, Pierre Latouche, Victor Elvira, Sarah
Filippi, Chris Oates.

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
sceptics to comment on all of these subjects and more.

Please stay informed on the series by joining the Google group or following
us on Twitter.

Registration for Christian Robert's 13th May talk 'Component-wise
approximate Bayesian computation via Gibbs-like steps' is already open.
https://sites.google.com/view/laplacesdemon/home
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