{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T15:28:01Z","timestamp":1781018881326,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":16,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T00:00:00Z","timestamp":1774224000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/legalcode"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,3,23]]},"DOI":"10.1145\/3748522.3779833","type":"proceedings-article","created":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T14:17:49Z","timestamp":1781014669000},"page":"687-696","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["IoT Participants Clustering to Reduce Heterogeneity and Accelerate Federated Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5254-6529","authenticated-orcid":false,"given":"Hamza","family":"Safri","sequence":"first","affiliation":[{"name":"Berger-levrault, Labege, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7056-1175","authenticated-orcid":false,"given":"Mohamed Mehdi","family":"Kandi","sequence":"additional","affiliation":[{"name":"Berger-levrault, Labege, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7005-3672","authenticated-orcid":false,"given":"Youssef","family":"Miloudi","sequence":"additional","affiliation":[{"name":"Berger-levrault, Limonest, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2623-6922","authenticated-orcid":false,"given":"Denis","family":"Trystram","sequence":"additional","affiliation":[{"name":"Grenoble university, Grenoble, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2611-8206","authenticated-orcid":false,"given":"Frederic","family":"Desprez","sequence":"additional","affiliation":[{"name":"Grenoble university, Grenoble, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,9]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2020.2988604"},{"key":"e_1_3_2_1_2_1","first-page":"19586","article-title":"-b20. An Efficient Framework for Clustered Federated Learning","volume":"33","author":"Ghosh Avishek","year":"2020","unstructured":"Avishek Ghosh, Jichan Chung, Dong Yin, and Kannan Ramchandran. 2020-b20. An Efficient Framework for Clustered Federated Learning. Advances in Neural Information Processing Systems, 33, 19586\u201319597.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_3_1","unstructured":"Farzin Haddadpour and Mehrdad Mahdavi. 2019. On the Convergence of Local Descent Methods in Federated Learning. arXiv e-prints arXiv-1910."},{"key":"e_1_3_2_1_4_1","unstructured":"Tzu-Ming Harry Hsu Hang Qi and Matthew Brown. 2019. Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification. arXiv preprint arXiv:1909.06335."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2019.103291"},{"key":"e_1_3_2_1_6_1","unstructured":"Yihan Jiang Jakub Kone\u010dn\u1ef3 Keith Rush and Sreeram Kannan. 2019. Improving Federated Learning Personalization via Model Agnostic Meta Learning. arXiv preprint arXiv:1909.12488."},{"key":"e_1_3_2_1_7_1","unstructured":"Mikhail Khodak Maria-Florina F Balcan and Ameet S Talwalkar. 2019. Adaptive Gradient-Based Meta-Learning Methods. Advances in Neural Information Processing Systems 32."},{"key":"e_1_3_2_1_8_1","volume-title":"Fedmd: Heterogenous Federated Learning via Model Distillation. arXiv preprint arXiv:1910.03581.","author":"Li Daliang","year":"2019","unstructured":"Daliang Li and Junpu Wang. 2019. Fedmd: Heterogenous Federated Learning via Model Distillation. arXiv preprint arXiv:1910.03581."},{"key":"e_1_3_2_1_9_1","unstructured":"Brendan McMahan Eider Moore Daniel Ramage Seth Hampson and Blaise Aguera y Arcas. 2017. Communication-Efficient Learning of Deep Networks from Decentralized Data. In Artificial intelligence and statistics. PMLR 1273\u20131282."},{"key":"e_1_3_2_1_10_1","volume-title":"Proceedings of the 29th Conference on Neural Information Processing Systems (NIPS)","author":"McMahan H Brendan","year":"2016","unstructured":"H Brendan McMahan, FX Yu, P Richtarik, AT Suresh, and D Bacon. 2016. Federated Learning: Strategies for Improving Communication Efficiency. In Proceedings of the 29th Conference on Neural Information Processing Systems (NIPS), Barcelona, Spain, 5\u201310."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CCGrid54584.2022.00066"},{"key":"e_1_3_2_1_12_1","volume-title":"Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization under Privacy Constraints","author":"Sattler Felix","unstructured":"Felix Sattler, Klaus-Robert M\u00fcller, and Wojciech Samek. 2020. Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization under Privacy Constraints. IEEE transactions on neural networks and learning systems, 32, 8, 3710\u20133722."},{"key":"e_1_3_2_1_13_1","volume-title":"On the Byzantine Robustness of Clustered Federated Learning. In ICASSP 2020\u20132020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 8861\u20138865","author":"Sattler Felix","year":"2020","unstructured":"Felix Sattler, Klaus-Robert M\u00fcller, Thomas Wiegand, and Wojciech Samek. 2020. On the Byzantine Robustness of Clustered Federated Learning. In ICASSP 2020\u20132020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 8861\u20138865."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20819"},{"key":"e_1_3_2_1_15_1","volume-title":"Proceedings of the Web Conference","author":"Yang Chengxu","year":"2021","unstructured":"Chengxu Yang, Qipeng Wang, Mengwei Xu, Zhenpeng Chen, Kaigui Bian, Yunxin Liu, and Xuanzhe Liu. 2021. Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Sata. In Proceedings of the Web Conference 2021, 935\u2013946."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2020.2996612"}],"event":{"name":"SAC '26: 41st ACM\/SIGAPP Symposium on Applied Computing","location":"Grand Hotel Palace Thessaloniki Greece","acronym":"SAC '26","sponsor":["SIGAPP ACM Special Interest Group on Applied Computing"]},"container-title":["Proceedings of the 41st ACM\/SIGAPP Symposium on Applied Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3748522.3779833","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T14:45:39Z","timestamp":1781016339000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3748522.3779833"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,23]]},"references-count":16,"alternative-id":["10.1145\/3748522.3779833","10.1145\/3748522"],"URL":"https:\/\/doi.org\/10.1145\/3748522.3779833","relation":{},"subject":[],"published":{"date-parts":[[2026,3,23]]},"assertion":[{"value":"2026-06-09","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}