Call for Papers
Call for Papers
Deadline for submissions: 01.09.2023 (23:59 AoE)
Notification of acceptance: Early to mid November
Please join for the 7th Northern Lights Deep Learning Conference (NLDL) on 9-11 January 2024 in Tromsø, Norway, organized by Visual Intelligence and the UiT Machine Learning Group.
We look forward to gathering the deep learning community again in the cool arctic air for a physical conference.
In addition, the NLDL winter school, which is a part of the NORA research school http://nora.ai, starts at Jan 8 and ends at Jan 12 and incorporates events during the main conference days. The winter school includes scientific topics, industry event, women in AI event, and transferrable skills. More information coming soon at http://www.nldl.org/winter-school.
We invite submissions presenting new and original research on all aspects of Deep Learning. The topics include but are not limited to the following:
General Machine Learning (active learning, clustering, online learning, ranking, reinforcement learning, supervised, semi- and self-supervised learning, time series analysis, etc.)
General Deep Learning (architectures, generative models, deep reinforcement learning, etc.)
Optimization (convex and non-convex optimization, matrix/tensor methods, stochastic, online, non-smooth, composite, etc.)
Probabilistic methods (Bayesian methods, variational inference, graphical models, etc.)
Social and economic aspects of Machine Learning (accountability, causality, fairness, privacy, robustness, interpretability, etc.)
Applications (vision, language, signals, speech and audio, etc.)
Deep Learning for Sciences (biology and medicine, environment and ecology, physics, etc.)
As always, we are happy to have top international speakers. This year, for instance
Mark Girolami – University of Cambridge/Alan Turing Institute
Narges Razavian – New York University
Mathilde Caron – Google Research
A tentative program will be available soon. We hope to see many participants for a nice scientific gathering on the “north pole”, including social events, and hopefully some northern lights
How to submit a contribution
We invite participants to submit in PDF format either
a 2-page extended abstract (non-archival) or
a 6-page full paper (included in proceedings)
in the area of Deep Learning. References can go beyond the page limit.
All submissions will undergo double-blind peer review. It will be up to the authors to ensure the proper anonymization of their paper. Do not include any names or affiliations. Refer to your own past work in the third-person, or if needed insert a blank reference. Accepted contributions will be accepted as contributing talks or poster presentations.
A ZIP archive with a LaTeX template can be downloaded here.
Reference instructions
References need to include a DOI (if it exists)
When citing arXiv papers, the authors need to check if the paper has been published. If there is a published version of the paper, it should be cited instead of the arXiv version.
Additional information
We allow authors to upload a preprint of the submitted papers to arXiv
For the camera ready version of accepted papers, we allow the authors to add a 7th page to their paper in order to address requests from the reviewers
At least one author must register for the conference and present their work in person. If the covid-situation should change dramatically, then we will inform about any changes in this policy and will inform the registered participants
Follow the following link to submit your submission (both full papers and extended abstracts):
Proceedings
There will be a peer-review process for the NLDL submissions and the 6 page contributions are to be considered as 'full' publications. The proceedings will be published through Septentrio Academic Publishing. The proceedings have been accepted as a Level 1 publication in the Norwegian system.
Copyright for accepted papers
Authors of accepted extended abstracts (non-archival submissions) retain full copyright of their work, and acceptance of such a submission does not preclude publication of the same material in another journal or conference.
Papers aimed for proceedings should follow general dual submission policies and submissions that are identical or substantially similar to papers that are in submission to, have been accepted to, or have been published in other archival conferences, journals, workshops, etc. will be rejected. Authors should clearly state any overlapping published or submitted work at the time of submission. Authors should ensure that they are not violating any other venue dual submission policies. Papers in proceedings will be assigned the CCBY 4.0 license.
Questions & Problems
For questions about the submission process or problems with the submission side, please contact Sigurd Løkse: sigurd.lokse@uit.no.