[UAI] Last CFP - "I can't believe it is not better" workshop at NeurIPS 2022

Do you have results that you can't believe are not better? Well, we are sorry - but sometimes we can learn more from surprising negative results. Announcing the 3rd edition of "I can't believe it is not better" workshop at NeurIPS 2022. This time focusing on "Understanding Deep Learning Through

[UAI] Laplace's Causal Demon Webinar Series 28 Feb - 9 Mar

ision Making <https://criteo.zoom.us/webinar/register/WN_c1DNRco8RPyrvJCuKPqc9w> 9 March 2022 David Rohde <http://goog_556269291/> Criteo Causal Inference is (Bayesian) Inference - A beautifully simple idea that not everyone accepts <https://criteo.zoom.us/webinar/register/WN_LhLBWnB

[UAI] Graph Machine Learning in Industry Webinar

Criteo AI Lab is excited to be presenting Graph Machine Learning in Industry. Please join us on Thursday, September 23rd, at 17:00 Paris time. Registration is now open: https://sites.google.com/view/graph-ml-in-industry/home Many problems in data mining, machine learning, and computer science c

[UAI] BCIRWIS 2021: Bayesian causal inference for real world interactive systems - (KDD 2021 Workshop)

Call For Papers (reminder) BCIRWIS 2021: Bayesian causal inference for real world interactive systems - (KDD 2021 Workshop) https://bcirwis2021.github.io/cfp.html Deadline extended to May 20 2021 Increasingly we use machine learning to build interactive systems that learn from past actions and the

[UAI] Call For Papers BCIRWIS 2021: Bayesian causal inference for real world interactive systems - (KDD 2021 Workshop)

Call For Papers BCIRWIS 2021: Bayesian causal inference for real world interactive systems - (KDD 2021 Workshop) Increasingly we use machine learning to build interactive systems that learn from past actions and the reward obtained. Theory suggests several possible approaches, such as contextua

[UAI] Bayesian Machine Learning at Scale Webinar

Laplace's Demon: Bayesian Machine Learning at Scale has a few announcements. Firstly registration is now open for Jake Hofman 17 June talk: "How visualizing inferential uncertainty can mislead readers about treatment effects in scientific results". Jake is a Senior Principal Researcher at Mic

[UAI] Bayesian Machine Learning at Scale Webinar Starting Wed 13 May

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