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The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks
- Source :
- ACM SIGCOMM Computer Communication Review, Vol. 51, No. 3, pp. 9-16, 2021
- Publication Year :
- 2021
-
Abstract
- During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments. This poses the need to count on new generations of students, researchers and practitioners with a solid background in ML applied to networks. During 2020, the International Telecommunication Union (ITU) has organized the "ITU AI/ML in 5G challenge'', an open global competition that has introduced to a broad audience some of the current main challenges in ML for networks. This large-scale initiative has gathered 23 different challenges proposed by network operators, equipment manufacturers and academia, and has attracted a total of 1300+ participants from 60+ countries. This paper narrates our experience organizing one of the proposed challenges: the "Graph Neural Networking Challenge 2020''. We describe the problem presented to participants, the tools and resources provided, some organization aspects and participation statistics, an outline of the top-3 awarded solutions, and a summary with some lessons learned during all this journey. As a result, this challenge leaves a curated set of educational resources openly available to anyone interested in the topic.
Details
- Database :
- arXiv
- Journal :
- ACM SIGCOMM Computer Communication Review, Vol. 51, No. 3, pp. 9-16, 2021
- Publication Type :
- Report
- Accession number :
- edsarx.2107.12433
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1145/3477482.3477485