Connectionists: CFP: 2nd Symposium on Advances in Approximate Bayesian Inference (AABI 2019)

[Thang Bui]

We invite researchers in machine learning and statistics to participate in
the:

*2nd Symposium on Advances in Approximate Bayesian Inference *
Sunday December 8, 2019, Vancouver, Canada
www.approximateinference.org

Submission deadline: *11 October, 2019*


*1. Call for Participation*

We invite researchers to submit their recent work on the development,
analysis, or application of approximate Bayesian inference. A submission
should take the form of an extended abstract of 2-4 pages in PDF format
using the PMLR one-column style [
http://approximateinference.org/pmlr/aabi_template.zip ]. For questions and
troubleshooting, visit CTAN [
https://ctan.org/tex-archive/macros/latex/contrib/jmlr ]. The review
process will be double-blind. Author names need to be anonymized and
references may extend as far as needed beyond the 4-page upper limit. If
authors' research has previously appeared in a journal, workshop, or
conference (including the NeurIPS 2019 conference), their symposium
submission should extend that previous work. Submissions may include a
supplement/appendix, but reviewers are not responsible for reading any
supplementary material.

All submissions will be reviewed by at least three reviewers from the
field. Accepted submissions will be accepted to presentation only. The
authors of selected submissions will be invited to publish their paper in a
PMLR volume. We aim to keep a general inclusive nature of the symposium for
presentations. However, we will only invite the top-rated accepted papers
to be published through PMLR.

Papers should be submitted by 11 October through OpenReview at 23:59 GMT [
https://openreview.net/group?id=approximateinference.org/AABI/2019/Symposium ].
Final versions of the symposium submissions are due by 5 December, and will
be posted on the symposium website.

If you have any questions, please contact us at aabisymposium2019 at gmail.com
.


*2. Key Dates*

Paper submission: 11 October 2019 (23:59 GMT)
Acceptance notification: 8 November 2019
Final paper submission: 5 December 2019


*3. Symposium Overview*

In recent years, there have been numerous advances in approximate inference
methods, which have enabled Bayesian inference in increasingly challenging
scenarios involving complex probabilistic models and large datasets. The
2nd Symposium on Advances in Approximate Bayesian Inference (AABI) will
discuss this impact of Bayesian inference, connecting both variational and
Monte Carlo methods with other fields. We encourage submissions that relate
Bayesian inference to the fields of reinforcement learning, causal
inference, decision processes, Bayesian compression, or differential
privacy, among others. We also encourage submissions that contribute to
connecting different approximate inference methods.

This symposium is a continuation of past years events:
+ 1st Symposium on Advances in Approximate Bayesian Inference (2018)
+ NIPS 2017 Workshop: Advances in Approximate Bayesian Inference
+ NIPS 2016 Workshop: Advances in Approximate Bayesian Inference
+ NIPS 2015 Workshop: Advances in Approximate Bayesian Inference
+ NIPS 2014 Workshop: Advances in Variational Inference


*4. Invited Speakers and Panelists*

Invited speakers:
Emily Fox (University of Washington)
Michael Gutmann (University of Edinburgh)
Sergey Levine (UC Berkeley)
Qiang Liu (University of Texas at Austin)
Christian Robert (Ceremade - Université Paris-Dauphine)
Michalis Titsias (DeepMind)
Rianne van den Berg (University of Amsterdam)

Panel:
Moderator: Frank Wood (University of British Columbia)
Barbara Engelhardt (Princeton University)
James Hensman (Prowler.io)
Radford Neal (University of Toronto)
Christian Robert (Ceremade - Université Paris-Dauphine)
Sinead Williamson (University of Texas at Austin)



Symposium organizers:
Thang Bui (University of Sydney / Uber)
Adji Dieng (Columbia University)
Dawen Liang (Netflix)
Francisco Ruiz (University of Cambridge / Columbia University)
Cheng Zhang (Microsoft Research)

Advisory committee:
David Blei (Columbia University)
Stephan Mandt (University of California, Irvine)
James McInerney (Netflix)
Dustin Tran (Google Brain / Columbia University)
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20190816/9922e5b4/attachment.html>