Call For Papers

Call for Papers


We invite contributions on all aspects of machine learning in open domains, including, but not limited to:

  • Evaluation of Machine Learning in and for open worlds, including: existing or proposed benchmarks, evaluation methodology and metrics.

  • Machine learning approaches for tackling key challenges of open worlds, such as transfer learning, lifelong learning, domain adaptation and generalization.

  • Machine learning systems, software, and real-world examples of machine learning in open worlds.

  • Machine learning in open worlds related to language, vision, interaction, and other forms or modalities.

  • We welcome both theoretical and empirical contributions in all relevant areas listed above.


Submissions

We invite the submission of 4-page papers that describe original work or synthesize a previously published larger body of work that make a meaningful contribution to learning in artificial open worlds.

Submissions should be anonymized for double-blind review, and should be formatted following the ICML 2020 style and author instructions where applicable. The 4-page limit excludes references and supplementary material.

Paper submission is electronic via the CMT system: http://cmt3.research.microsoft.com/LAOW2020

Acceptance decisions will be made based on a minimum of two double blind reviews.


Important Dates

  • Submission deadline: 22 June 2020

  • Notification of acceptance: 6 July 2020

  • Final version of accepted papers due: 10 July 2020 (final versions will be posted on the workshop website)

  • Workshop: 17 or 18 July 2020

All deadlines are specified as anywhere on Earth.