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The graph neural networking challenge: a worldwide competition for education in AI/ML for networks

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.
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https://hal.inria.fr/hal-03346696
Contributor : François Taïani Connect in order to contact the contributor
Submitted on : Thursday, September 16, 2021 - 3:19:36 PM
Last modification on : Friday, August 5, 2022 - 2:54:52 PM
Long-term archiving on: : Friday, December 17, 2021 - 7:14:34 PM

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José Suárez-Varela, Miquel Ferriol-Galmés, Albert López, Paul Almasan, Guillermo Bernárdez, et al.. The graph neural networking challenge: a worldwide competition for education in AI/ML for networks. Computer Communication Review, 2021, 51 (3), pp.9-16. ⟨10.1145/3477482.3477485⟩. ⟨hal-03346696⟩

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