The 27th Annual Conference on Learning Theory (COLT 2014) will take
place in Barcelona, Spain, on June 13-15, 2014
We invite submissions of papers addressing theoretical aspects of
machine learning and related topics. Submissions by authors who are
new to COLT are encouraged. We strongly support a broad definition of
learning theory, including, but not limited to:
• Design and analysis of learning algorithms and their generalization ability
• Computational complexity of learning
• Optimization procedures for learning
• Unsupervised, semi-supervised learning, and clustering
• Online learning
• Interactive learning
• Kernel Methods
• High dimensional and non-parametric empirical inference, including
sparsity methods
• Planning and control, including reinforcement learning
• Learning with additional constraints: E.g. privacy, time or memory
budget, communication
• Learning in other settings: E.g. social, economic, and game-theoretic
• Analysis of learning in related fields: natural language processing,
neuroscience, bioinformatics, privacy and security, machine vision,
data mining, information retrieval.
We are also interested in papers that include viewpoints that are new
to the COLT community. We welcome experimental and algorithmic papers
provided they are relevant to the focus of the conference by
elucidating theoretical results. Also, while the primary focus of the
conference is theoretical, papers can be strengthened by the inclusion
of relevant experimental results.
COLT will award both best paper and best student paper awards. Best
student papers must be authored or coauthored by a student. Authors
must indicate (using a footnote on the first page of the paper) at
submission time if they wish their paper to be eligible for a student
award. This does not preclude the paper to be eligible for the best
paper award. The program committee may decline to make these awards,
or may split them among several papers.
Papers that have previously appeared in journals or at other
conferences, or that are being submitted to other conferences, are not
appropriate for COLT. Papers that include work that has already been
submitted for journal publication may be submitted to COLT, as long as
the papers have not been accepted for publication by the COLT
submission deadline (conditionally or otherwise) and that the paper is
not expected to be published before the COLT conference (June 2014).
Accepted papers will be published electronically, in the JMLR Workshop
and Conference Proceedings series.
Rebuttal Phase
As in the previous years, we will have 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. Final
acceptance/rejection decision will be made a week later.
Open Problems Session:
We also invite submission of open problems. A separate call for open
problems will be available at the conference website:
http://orfe.princeton.edu/
Submission Instructions:
Submissions are limited to 12 JMLR-formatted pages, plus 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.
Important Dates:
• Paper submission deadline: February 7th, 2014, 11:00 PM EST
• Author response period: April 5-10, 2014
• Author notification: April 19, 2014
• Conference: June 13-15, 2014
On behalf of the COLT 2014 organizers,
Program Chairs
• Maria-Florina Balcan (Georgia Institute of Technology)
• Csaba Szepesvári (University of Alberta)
Local Arrangements Chairs
• Sébastien Bubeck (Princeton University)
• Gábor Lugosi (ICREA and Pompeu Fabra University)
Publication Chair
• Vitaly Feldman (IBM Almaden Research Center)
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