COLT: Computational Learning Theory

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Past:   Proceedings on DBLP

Future:  Post a CFP for 2019 or later   |   Invite the Organizers Email

 
 

All CFPs on WikiCFP

Event When Where Deadline
COLT 2018 Computational Learning Theory
Jul 5, 2018 - Jul 9, 2018 Stockholm, Sweden Feb 16, 2018
COLT 2017 Computational Learning Theory
Jul 7, 2017 - Jul 10, 2017 Amsterdam, Netherlands Feb 17, 2017
COLT 2016 Conference on Learning Theory
Jun 23, 2016 - Jun 26, 2016 New York, NY, USA Feb 12, 2016
COLT 2015 Conference on Learning Theory 2015
Jul 3, 2015 - Jul 3, 2015 Paris, France Feb 19, 2015
COLT 2014 Conference on Learning Theory
Jun 13, 2014 - Jun 15, 2014 Barcelona, Spain Feb 7, 2014
COLT 2013 26th Annual Conference on Learning Theory
Jun 12, 2013 - Jun 14, 2013 Princeton, NJ, USA Feb 8, 2013
COLT 2012 25th Annual Conference on Learning Theory
Jun 25, 2012 - Jun 27, 2012 Edinburgh, Scotland Feb 14, 2012
COLT 2011 The 24rd Annual Conference on Learning Theory
Jul 9, 2011 - Jul 11, 2011 Budapest, Hungary Feb 11, 2011
COLT 2010 The 23rd International Conference on Learning Theory
Jun 27, 2010 - Jun 29, 2010 Haifa, Israel Feb 19, 2010
COLT 2009 The 22nd Annual Conference on Learning Theory
Jun 18, 2009 - Jun 21, 2009 Montreal, Canada Feb 13, 2009
COLT 2008 Conference on Learning Theory
Jul 9, 2008 - Jul 12, 2008 Helsinki, Finland Feb 20, 2008
 
 

Present CFP : 2018

The 31st Annual Conference on Learning Theory (COLT 2018) will take place in Stockholm, Sweden, on July 5-9, 2018 (with a welcome reception on the 4th), immediately before ICML 2018, which takes place in the same city. 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, semi-supervised, online and active learning
-Interactions with other mathematical fields
-Interactions with statistical physics
-Artificial neural networks, including deep learning
-High-dimensional and non-parametric statistics
-Learning with algebraic or combinatorial structure
-Geometric and topological data analysis
-Bayesian methods in learning
-Planning and control, including reinforcement learning
-Learning with system constraints: e.g. privacy, memory or communication budget
-Learning from complex data: e.g., networks, time series, etc.
-Learning in other settings: e.g. social, economic, and game-theoretic

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 Easychair submission form, 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 here.

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.

Open Problems Session:
We also invite submission of open problems. A separate call for open problems will be made available on the conference website.

Important Dates:
-Paper submission deadline: February 16, 2018, 11:00 PM EST
-Author feedback: April 18-21, 2018
-Author notification: May 2, 2018
-Conference: July 5-9, 2017 (welcome reception on the 4th)

Submission:
Papers should be submitted through EasyChair at https://easychair.org/conferences/?conf=colt2018

Program Chairs:
Sebastien Bubeck (Microsoft Research)
Philippe Rigollet (MIT)
 

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