Connectionists: [Reminder] [CFP] Conference on Causal Learning and Reasoning (CLeaR 2023) - deadline: Oct 28

[Sara Magliacane]

*Reminder: *10 days to submission deadline (Oct 28 11:59pm AoE)


We invite submissions to the *2nd Conference on Causal Learning and
Reasoning* (CLeaR 2023, https://www.cclear.cc/2023), and welcome paper
submissions that describe new theory, methodology, and/or applications
relevant to any aspect of causal learning and reasoning in the fields of
artificial intelligence and statistics. Accepted papers will be published
in the Proceedings of Machine Learning Research (PMLR).
Key datesThe planned dates are as follows:

   - Paper submission deadline: Oct 28, 2022 11:59pm (Anywhere on Earth,
   AoE)
   - Reviews released: Dec 2, 2022
   - Author rebuttals due: Dec 9, 2022 11:59pm (AoE)
   - Final decisions: Jan 12, 2023
   - Camera-ready deadline: Feb 20, 2023 11:59pm (AoE)
   - Conference dates: Apr 11-14, 2023
   - Format: Hybrid with both virtual and physical attendance.

Submit at https://openreview.net/group?id=cclear.cc/CLeaR/2023/Conference.
Summary

Causality is a fundamental notion in science and engineering. In the past
few decades, some of the most influential developments in the study of
causal discovery, causal inference, and the causal treatment of machine
learning have resulted from cross-disciplinary efforts. In particular, a
number of machine learning and statistical analysis techniques have been
developed to tackle classical causal discovery and inference problems. On
the other hand, the causal view has been shown to facilitate formulating,
understanding, and tackling a broad range of problems, including domain
generalization, robustness, trustworthiness, and fairness across machine
learning, reinforcement learning, and statistics.

We invite papers that describe new theory, methodology and/or applications
relevant to any aspect of causal learning and reasoning in the fields of
artificial intelligence and statistics. Submitted papers will be evaluated
based on their novelty, technical quality, and potential impact.
Experimental methods and results are expected to be reproducible, and
authors are strongly encouraged to make code and data available. We also
encourage submissions of proof-of-concept research that puts forward novel
ideas and demonstrates potential for addressing problems at the
intersection of causality and machine learning.
Paper Submission

The proceedings track is the standard CLeaR paper submission track. Papers
will be selected via a rigorous double-blind peer-review process. All
accepted papers will be presented at the Conference as contributed talks or
as posters and will be published in the Proceedings.

Topics of submission may include, but are not limited to:

   - Machine learning building on causal principles
   - Causal discovery in complex environments
   - Efficient causal discovery in large-scale datasets
   - Causal effect identification and estimation
   - Causal generative models for machine learning
   - Unsupervised and semi-supervised deep learning connected to causality
   - Machine learning with heterogeneous data sources
   - Benchmark for causal discovery and causal reasoning
   - Reinforcement learning
   - Fairness, accountability, transparency, explainability,
   trustworthiness, and recourse
   - Applications of any of the above to real-world problems
   - Foundational theories of causation

Physical Attendance

The CLeaR 2023 organizing committee prioritizes the safety and health of
our community. We are still considering the format of the CLeaR 2023
conference. It will be preferably held as a hybrid conference with no
mandatory physical attendance, but we also keep a backup plan of making the
conference virtual in case of new pandemic situations. After our final
decision, we will announce the format of the conference on the website.
Thank you for your patience and understanding.
Formatting and Supplementary Material

Submissions are limited to 12 single-column PMLR-formatted pages, plus
unlimited additional pages for references and appendices. Authors of
accepted papers will have the option of opting out of the proceedings in
favor of a 1-page extended abstract, which will point to an open access
archival version of the full paper reviewed for CLeaR. You can also submit
a single file of additional supplementary material separately, which may be
either a pdf file (containing proof details, for instance) or a zip file
that can include multiple files of all formats (such as code or videos).
Note that reviewers are under no obligation to examine the supplementary
material.

Please format the paper using the official LaTeX style files
<https://drive.google.com/drive/folders/1n9RhQ4rJ9zxjXEyFovJAdakCZwNMKF3j?usp=sharing>.
We do not support submission in formats other than LaTeX. Please do not
modify the layout given by the style file.

Submissions will be through OpenReview (
https://openreview.net/group?id=cclear.cc/CLeaR/2023/Conference) and will
be open approximately 4-6 weeks before the paper submission deadline.
Anonymization Requirements

The CLeaR review process is double-blind: reviewers and authors will both
stay anonymous to each other during the review process. We use OpenReview
to host papers; however, public discussions are not allowed during the
review process. The review comments are only visible to program chairs,
area chairs, and reviewers with submitted review comments. Papers will be
desk-rejected if they contain any information that can violate the
double-blind reviewing policy, such as the author names or their
affiliations, acknowledgements, or links that can infer any author’s
identity or institution. Self-citations are allowed as long as anonymity is
preserved. It is up to the author’s discretion how best to preserve
anonymity when including self-citations. Possibilities include: leaving out
a self-citation, including it but replacing the citation text with “removed
for anonymous submission,” or leaving the citation as-is. We recommend
leaving in a moderate number of self-citations for published or otherwise
well-known work.

Revisions are allowed in the submission system until the paper submission
deadline. Changes will not be allowed afterwards.

We strongly discourage advertising the preprint on social media or in the
press while under submission to CLeaR. Preprints must not be explicitly
identified as an CLeaR submission at any time during the review period
(i.e., from the abstract submission deadline until the notification of the
accept/reject decision).
Dual Submissions

CLeaR does not allow double submissions. Namely, submissions should not
have been previously published in or submitted to a journal or the
proceedings of another conference at any point during the CLeaR review
process. Submissions to workshops or other non-archival venues (without a
proceedings) will not be considered as dual submissions. Submissions as
extended abstracts with 5 pages or less will not be considered a concurrent
submission either. Authors may submit anonymized work to CLeaR that is
already available as a preprint (e.g., on arXiv) without citing it. Tech
reports (including reports on sites such as arXiv) do not count as prior
publication. It is acceptable to have a substantially extended version of
the submitted paper under consideration simultaneously for journal
publication, so long as the journal version’s planned publication date is
after our publication (April 13, 2023, tentatively), and it does not
violate the journal's policy, the journal submission does not interfere
with CLeaR right to publish the paper, and the situation is clearly
described at the time of CLeaR submission. Please describe the situation in
the appropriate box on the submission page (and do not include author
information in the submission itself, to avoid accidental unblinding).
Authors are also allowed to give talks to restricted audiences on the
work(s) submitted to CLeaR during the review.

All accepted papers will be presented at the Conference either as
contributed talks or as posters, and will be published in the CLeaR
Conference Proceedings in the Journal of Machine Learning Research Workshop
and Conference Proceedings series. Papers for talks and posters will be
treated equally in publication.
Confidentiality

The reviewers and area-chairs will have access to papers and supplementary
materials that are assigned to them.

The program chairs and workflow chairs will have access to all the papers.
Everyone having access to papers and supplementary materials will be
instructed to keep them confidential during the review process and delete
them after the final decisions.

Reviews will be visible to area chairs, program chairs, and workflow chairs
throughout the process. At any stage of the process, author names will not
be known to the reviewers or area chairs, but only visible to program
chairs. Reviewer names are visible to the area chair (and program chairs),
but the reviewers will not know names of other reviewers.

Mihaela van der Shaar, Cheng Zhang & Dominik Janzing
CLeaR 2023 Program Chairs

Francesco Locatello & Peter Spirtes
CLeaR 2023 General Chairs
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