6th International Conference on Learning Representations
5:00pm Eastern Standard Time, October 27, 2017
Vancouver Convention Center, Vancouver, BC, Canada, April 30 - May 3, 2018
The performance of machine learning methods is heavily dependent on the choice of data representation (or features) on which they are applied. The rapidly developing field of deep learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. We take a broad view of the field and include topics such as feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization. The range of domains to which these techniques apply is also very broad, from vision to speech recognition, text understanding, gaming, music, etc.
A non-exhaustive list of relevant topics:
The program will include keynote presentations from invited speakers, oral presentations, and posters.
ICLR features two tracks: a Conference Track and a Workshop Track. Submissions of extended abstracts to the Workshop Track will be accepted after the decision notifications for Conference Track submissions are sent. A future call for extended abstracts will provide more details on the Workshop Track.
Some of the submitted Conference Track papers that are not accepted to the conference proceedings will be invited for presentation in the Workshop Track.
1) Submissions will be double blind, meaning that reviewers cannot see author names when performing reviews, and authors cannot see reviewer names. While we will still use Open Review to host papers and allow for public discussions that can be seen by all, comments that are posted remain anonymous.
2) If someone wants to cite a paper during the review period, OpenReview will provide a BibTeX entry that does not list the authors, but does give the title, year and URL. Only at the end of the review period will the authors be revealed.
3) We will have only one round of review process, where the reviewers will provide their assessment of the paper. There will still be a discussion period between the authors and reviewers after the initial review round.
By October 27 - 5:00 pm EST, authors are asked to submit their paper to:
The initial paper needs to be submitted by this date, however authors are encouraged to update their submission as desired. Note that the initial paper that will be reviewed is based on that submitted by the October 27th deadline. There is no strict limit on paper length. However, we strongly recommend keeping the paper at 8 pages, plus 1 page for the references and as many pages as needed in an appendix section (all in a single pdf). The appropriateness of using additional pages over the recommended length will be judged by reviewers. Authors are encouraged to participate in the public discussion of their paper, as well as 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 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 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-peered reviewed websites (like arXiv) or that have been presented at workshops (i.e., venues that do not have a publication proceedings) do not violate the policy. The policy is enforced during the whole reviewing process period.
Authors have the right to withdraw papers at any time until paper notification. However, once a paper has been submitted to ICLR, a withdrawn paper will be moved to a “withdrawn papers” section and thus will not get reviewed or receive a paper decision. However it will continue to get hosted by OpenReview and be publically visible.
Yoshua Bengio, Université de Montreal
Yann LeCun, New York University and Facebook
Tara Sainath, Google
Iain Murray, University of Edinburgh
Marc’Aurelio Ranzato, Facebook
Oriol Vinyals, Google DeepMind
Aaron Courville, Université de Montreal
Hugo Larochelle, Google
The organizers can be contacted at firstname.lastname@example.org