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Specific informations of {{{1}}}'s site:
- [[{{{1}}}:Hardware|Hardware]]
- [[{{{1}}}:Network|Network]]
- [[{{{1}}}:Storage|Storage]]
- [[{{{1}}}:External access|External access]]
- [[{{{1}}}:People|People]]
- [[{{{1}}}:Administration|Administration]]
Direct access to resources for {{{1}}}'s site:
- reservation state (monika) and reservation history (drawgantt) via OAR
- available resources via Ganglia
- critical services via Nagios
- opened bugs via BugZilla
- support-staff via mail
Shortcuts to global tools and informations:
- support procedures to report bugs or ask for enhancements
- global reservation state and global reservation history via OARgrid.
- registered users via UMS
Latest updated publications Five random publications that benefited from Grid'5000 (at least 2940 overall):
- Barbara Gendron, Gaël Guibon. SEC: Context-Aware Metric Learning for Efficient Emotion Recognition in Conversation. Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis (WASSA at ACL 2024), Aug 2024, Bangkok, Thailand. hal-04702997 view on HAL pdf
- Hugo Thomas, Guillaume Gravier, Pascale Sébillot. One-shot relation retrieval in news archives: adapting N-way K-shot relation classification for efficient knowledge extraction. KES 2024 - 28th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Sep 2024, Seville, Spain. pp.1060-1069. hal-04708239 view on HAL pdf
- Célia Mahamdi. Multi-Consensus distribué : agrégation et révocabilité. Réseaux et télécommunications cs.NI. Sorbonne Université, 2024. Français. NNT : 2024SORUS426. tel-04919363 view on HAL pdf
- Mathis Valli, Alexandru Costan, Cédric Tedeschi, Loïc Cudennec. Towards Efficient Learning on the Computing Continuum: Advancing Dynamic Adaptation of Federated Learning. FlexScience 2024 - 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures, Jun 2024, Pisa, Italy. pp.42-49, 10.1145/3659995.3660042. hal-04698619v2 view on HAL pdf
- Mai Huong Do, Millian Poquet, Georges da Costa. FedE-ator : A framework for energy consumption analysis of federated learning in distributed systems. Compas’2025 : Parallélisme / Architecture/ Système, Jul 2025, Bordeaux, France. hal-05181877 view on HAL pdf
Latest updated experiments {{#experiments: 5|{{{1}}}}}
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