ICLR 2022 - Call For Papers
Virtual conference, Mon Apr 25th through Fri the 29th
We invite submissions to the 2022 International Conference on Learning Representations, and welcome paper submissions from all areas of machine learning and deep learning.
For any information needed that is not listed below, please submit questions using this link: https://iclr.cc/Help/Contact.
Out of 784 ranked conferences, the CORE 2021 conference ranking assessment of the ICLR conference positioned ICLR in the top 7% of academic conferences, with ICLR receiving the highest-ranking assessment of an A*. The CORE Conference Ranking provides assessments of major conferences in the computing disciplines. Conference rankings are determined by a mix of indicators, including citation rates, paper submission and acceptance rates, and the visibility and research track record of the key people hosting the conference and managing its technical program.
The planned dates are as follow:
- Abstract submission: Sep 28, 2021
- Submission date: Oct 05, 2021
- Reviews released: Nov 07, 2021
- Author discussion period ends: Nov 21, 2021
- Final decisions: Jan 24, 2022
We consider a broad range of subject areas including feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization, as well as applications in vision, speech recognition, text understanding, robotics, health care, sustainability, music, games, computational biology, and others.
A non-exhaustive list of relevant topics:
- unsupervised, semi-supervised, and supervised representation learning
- representation learning for planning and reinforcement learning
- representation learning for computer vision and natural language processing
- metric learning and kernel learning
- sparse coding and dimensionality expansion
- hierarchical models
- optimization for representation learning
- learning representations of outputs or states
- Optimal transport
- theoretical issues in deep learning
- visualization or interpretation of learned representations
- implementation issues, parallelization, software platforms, hardware
- applications in audio, speech, robotics, neuroscience, computational biology, or any other field
- societal considerations of representation learning including fairness, safety, privacy, and interpretability
Double blind reviewing
Submissions will be double blind: reviewers cannot see author names when conducting reviews, and authors cannot see reviewer names. We use OpenReview to host papers and allow for public discussions that can be seen by all, comments that are posted by reviewers will remain anonymous. The program will include keynote presentations from invited speakers, oral presentations, and posters.
Authors can revise their paper as many times as needed up to the paper submission deadline. Changes to the paper will not be allowed while the paper is being reviewed. During the discussion phase (between area chairs, reviewers and authors), edits will again be allowed; a pdfdiff will be done against the submission at the paper submission deadline. Area chairs and reviewers reserve the right to ignore changes that are significant from the original scope of the paper. As in the past three years, workshops will have their own organisation and call for contributions.
This year we are asking authors to submit paper abstracts by the abstract submission deadline of 28 September 2021 05:00 PM PDT. The full paper submission deadline is 5 October 2021 05:00 PM PDT. Abstracts and papers must be submitted using the conference submission system at: https://openreview.net/group?id=ICLR.cc/2022/Conference. Abstracts submitted by the abstract submission deadline must be genuine, placeholder or duplicate abstracts will be removed.
- There will be a strict upper limit of 9 pages for the main text of the initial submission, with unlimited additional pages for citations.
- Authors may use as many pages of appendices (after the bibliography) as they wish, but reviewers are not required to read these.
Style files and Templates
To prepare your submission to ICLR 2022, please use the LaTeX style files provided at:
Authors are strongly encouraged to participate in the public discussion of their paper, as well as of any other paper submitted to the conference. Submissions and reviews are both anonymous. For detailed instructions about the format of the paper, please visit www.iclr.cc.
- Submissions to ICLR are uploaded on OpenReview, which enables public discussion. Official reviews are anonymous and publicly visible. During the public discussion phase, anybody who is logged in can post comments that are publicly visible, or restrict visibility to reviewers and up, ACs and up, or just PCs. In addition, the author of a comment can decide to post anonymously or not. Login is required before posting any comment.
- Once reviews have been posted, authors are encouraged to revise their paper until the paper submission deadline. Authors can participate in the discussion about their paper, as well as about any other paper submitted to the conference, at any time.
- Full reviews are posted by November 8, 2021. Reviews are anonymous and publicly visible in Open Review. Once the reviews are posted, authors are free to upload modifications to the paper during the two week discussion period.
- During the discussion period, if you choose to update the submission, a pdfdiff will be applied to compare new changes to the paper against the original submission. Area chairs and reviewers reserve the right to ignore changes that are significantly different from the original paper. In addition, during this period, any submission that is cited will be given an anonymous BibTex entry.
- After discussion there will be an internal discussion period amongst reviewers and ACs with the aim of summarising the review process, after which acceptance decisions are made. Papers that are not accepted will be considered non-archival, and may be submitted elsewhere (modified or not), although the OpenReview site will maintain the reviews, the comments, and links to the versions submitted to ICLR.
Code of Conduct
All ICLR participants, including authors, are required to adhere to the ICLR code of conduct (https://iclr.cc/public/CodeOfConduct). More detailed guidance for authors, reviewers, and all other participants will be made available in due course, and participation will require acknowledging and adhering to the provided guidelines.
Code of Ethics
All ICLR participants, including authors, are required to adhere to the ICLR Code of Ethics (https://iclr.cc/public/CodeOfEthics). All authors of submitted papers are required to read the Code of Ethics, adhere to it, and explicitly acknowledge this during the submission process. The Code of Ethics applies to all conference participation, including paper submission, reviewing, and paper discussion.
Dual Submission Policy
Submissions that are identical (or substantially similar) to versions that have been previously published, or accepted for publication, or that have been submitted in parallel to this or other conferences or journals, are not allowed and violate our dual submission policy. However, papers that cite previous related work by the authors and papers that have appeared on non-peer reviewed websites (like arXiv) or that have been presented at workshops (i.e., venues that do not have publication proceedings) do not violate the policy. The policy is enforced during the whole reviewing process period. Submission of the paper to archival repositories such as arXiv is allowed.
To allow citation of papers that are under review at ICLR2022, OpenReview provides BibTeX entries that do not list the authors, but does give the title, year and url. Author names are revealed at the end of the conference.
Authors have the right to withdraw papers from consideration at any time until paper notification. Before the paper submission deadline, if an author withdraws the paper it will be deleted from the OpenReview hosting site. However, note that after the paper submission deadline, if an author chooses to withdraw a submission, it will remain hosted by OpenReview in a publicly visible "withdrawn papers" section. Like on arXiv, submissions to ICLR cannot be deleted or modified. Withdrawn papers will be de-anonymized immediately.