Nectar Track
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The European Conference on Machine Learning and Principles and
Practice of Knowledge Discovery in Databases (ECML PKDD), the flagship
European machine learning and data science conference (15-19 September
2025), invites submissions to the Nectar Track.
The goal of the Nectar Track is to offer conference attendees a
compact overview of recent scientific advances at the frontier of
machine learning and data mining with other disciplines, as already
published in related conferences and journals. For researchers from
other disciplines, the Nectar Track offers a place to present their work
to the ECML-PKDD community and to raise the community’s awareness of AI
and data science results and open problems in their field. We invite
senior and junior researchers to submit summaries of their own work
published in various fields, including but not limited to artificial
intelligence, generative AI, big data analytics, bioinformatics, cyber
security, games, computational linguistics, natural language processing,
large language models, information retrieval, computer vision and image
analysis, geoinformatics, health informatics, database theory,
human-computer interaction, ethical aspects of artificial intelligence,
information and knowledge management, robotics, pattern recognition,
statistics, social network analysis, theoretical computer science,
uncertainty in AI, network science, complex systems science, and
computationally oriented sociology, economy and biology, as well as
critical data science/studies.
Acceptance criteria will also take into account the publication date
(cutoff date—up to 18 months old) and the quality of the conference
venue or journal. The authors of accepted papers are expected to attend
the conference and present their work. Accepted Nectar contributions
will be presented as oral presentations but not included in the
conference proceedings.
Key Dates and Deadlines
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Submission Deadline: June 30th, 2025
Author Notification: July 14th, 2025
*All deadlines expire on 23:59 AoE (UTC - 12)
Submission Guidelines
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Submission site:
https://cmt3.research.microsoft.com/ECMLPKDD2025
Submissions must be extended abstracts of 2-4 pages (including
references) and should be based on published work. The corresponding
original publication(s) should be clearly indicated. The relevance of
the work in the context of machine learning and data mining should be
clearly motivated.
Submissions should be formatted according to the Author
instructions, style files and copyright form that can be found in the
“Lecture Notes in Computer Science” (LNCS) Series. submitted through the
conference Microsoft CMT submission site (select from the menu the
Nectar track).
Contact
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For further information, please see the conference website or contact:
ecml-pkdd-2025-ne...@googlegroups.com