Connectionists: ICLR 2019 workshop on reproducibility in machine learning

[Rosemary Ke]

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Call for papers: ICLR 2019 workshop on reproducibility in machine learning.
Monday May 6, 2019. New Orleans

https://sites.google.com/view/icml-reproducibility-workshop/home
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Our aim in the following workshop is to raise the profile of these
questions in the community and to search for their answers. In doing so we
aim for papers focusing on the following topics: Analysis of the current
state of reproducibility in machine learning. Some examples of this include
experimental-driven investigations as in [1,2,3] Investigations and
proposals of proper experimental procedure and evaluation methodologies
which ensure reproducible and fair comparisons in novel literature [4]
Evidence-driven works investigating the importance of reproducibility in
machine learning and science in general Connections between the
reproducibility situation in Machine Learning and other fields Rigorous
replications, both failed and successful, of influential papers in the
Machine Learning literature. We will accept both short paper (4 pages) and
long paper (8 pages) submissions (not including references). Submissions
should be in the NIPS 2018 format. A few papers may be selected as oral
presentations, and the other accepted papers will be presented in a poster
session. There will be no proceedings for this workshop, however, upon the
author’s request, accepted contributions will be made available in the
workshop website. Submission are single-blind, peer-reviewed on OpenReview (
https://openreview.net/group?id=ICLR.cc/2019/Workshop/RML), and open to
already published work.

Organizers:

Anirudh Goyal (Mila, University of Montreal)
Alex Lamb (Mila, University of Montreal)
Nan Rosemary Ke (Mila, University of Montreal)
Olexa Bilaniuk (Mila, University of Montreal)
Yoshua Bengio (Mila, University of Montreal)
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