For authors

Call for papers

Call for papers

The 32nd Annual Conference on Learning Theory (COLT 2019) will take place in Phoenix, Arizona, June 25-28, 2019, as part of the ACM Federated Computing Research Conference, which also includes EC and STOC. We invite submissions of papers addressing theoretical aspects of machine learning and related topics. We strongly support a broad definition of learning theory, including, but not limited to:
- Design and analysis of learning algorithms
- Statistical and computational complexity of learning
- Optimization methods for learning
- Unsupervised and semi-supervised learning
- Interactive learning, planning and control, and reinforcement learning
- Online learning and decision-making under uncertainty
- Interactions of learning theory with other mathematical fields
- Artificial neural networks, including deep learning
- High-dimensional and non-parametric statistics
- Learning with algebraic or combinatorial structure
- Bayesian methods in learning
- Game theory and learning
- Learning with system constraints (e.g., privacy, computational, memory, communication)
- Learning from complex data: e.g., networks, time series
- Learning in other settings: e.g., computational social science, economics

Submissions by authors who are new to COLT are encouraged. While the primary focus of the conference is theoretical, the authors may support their analysis by including relevant experimental results.
All accepted papers will be presented in a single track at the conference. At least one of each paper’s authors should be present at the conference to present the work. Accepted papers will be published electronically in the Proceedings of Machine Learning Research (PMLR). The authors of accepted papers will have the option of opting-out of the proceedings in favor of a 1-page extended abstract. The full paper reviewed for COLT will then be placed on the arXiv repository.

Paper Awards:

COLT will award both best paper and best student paper awards. To be eligible for the best student paper award, the primary contributor(s) must be full-time students at the time of submission. For eligible papers, authors must indicate at submission time if they wish their paper to be considered for a student paper award. The program committee may decline to make these awards, or may split them among several papers.

Dual Submissions:

Submissions that are substantially similar to papers that have been previously published, accepted for publication, or submitted in parallel to other peer-reviewed conferences with proceedings may not be submitted to COLT. The same policy applies to journals, unless the submission is a short version of a paper submitted to a journal, and not yet published. Authors must declare such dual submissions either through the submission server, or via email to the program chairs.

Formatting:

Submissions are limited to 12 PMLR-formatted pages, plus unlimited additional pages for references and appendices. All details, proofs and derivations required to substantiate the results must be included in the submission, possibly in the appendices. However, the contribution, novelty and significance of submissions will be judged primarily based on the main text (without appendices), and so enough details, including proof details, must be provided in the main text to convince the reviewers of the submissions’ merits. Formatting and submission instructions can be found on the conference website: http://learningtheory.org/colt2019/.

Rebuttal Phase:

As in previous years, there will be a rebuttal phase during the review process. Initial reviews will be sent to authors before final decisions have been made. Authors will have the opportunity to provide a short response on the PC’s initial evaluation.

Important Dates:

All dates are in 2019.
- Paper submission deadline: February 1, 11:00 PM EST
- Author feedback: March 22-27
- Author notification: April 17
- Conference: June 25-28 (welcome reception on June 24)