{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T15:53:42Z","timestamp":1772726022141,"version":"3.50.1"},"reference-count":40,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,10,6]],"date-time":"2024-10-06T00:00:00Z","timestamp":1728172800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,10,6]],"date-time":"2024-10-06T00:00:00Z","timestamp":1728172800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100007601","name":"EU Horizon 2020","doi-asserted-by":"publisher","award":["101104278"],"award-info":[{"award-number":["101104278"]}],"id":[{"id":"10.13039\/501100007601","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,6]]},"DOI":"10.1109\/dsaa61799.2024.10722828","type":"proceedings-article","created":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T17:23:54Z","timestamp":1729790634000},"page":"1-10","source":"Crossref","is-referenced-by-count":1,"title":["CL-FML: Cluster-Based & Label-Aware Federated Meta-Learning for On-Demand Classification Tasks"],"prefix":"10.1109","author":[{"given":"Tahani","family":"Aladwani","sequence":"first","affiliation":[{"name":"University of Glasgow"}]},{"given":"Christos","family":"Anagnostopoulos","sequence":"additional","affiliation":[{"name":"University of Glasgow"}]},{"given":"Shameem P.","family":"Parambath","sequence":"additional","affiliation":[{"name":"University of Glasgow"}]},{"given":"Fani","family":"Deligianni","sequence":"additional","affiliation":[{"name":"University of Glasgow"}]}],"member":"263","reference":[{"key":"ref1","author":"Yoon","year":"2021","journal-title":"Fedmix: Approximation of mixup under mean augmented federated learning"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-12833-x"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/WCNC51071.2022.9771994"},{"key":"ref4","volume":"1","author":"Guo","year":"2023","journal-title":"Fedrc: Tackling diverse distribution shifts challenge in federated learning by robust clustering"},{"key":"ref5","author":"Zhang","year":"2023","journal-title":"A survey on class imbalance in federated learning"},{"key":"ref6","author":"Lu","year":"2022","journal-title":"Tackling imbalanced class in federated learning via class distribution estimation"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN54540.2023.10191845"},{"key":"ref8","author":"Lee","year":"2019","journal-title":"Learning to balance: Bayesian meta-learning for imbalanced and out- of-distribution tasks"},{"key":"ref9","first-page":"3557","article-title":"Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach","volume":"33","author":"Fallah","year":"2020","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS47774.2020.00032"},{"key":"ref11","author":"Yan","year":"2022","journal-title":"Federated clustering with gan- based data synthesis"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.hcc.2022.100068"},{"key":"ref13","first-page":"21 554","article-title":"Robust federated learning: The case of affine distribution shifts","volume":"33","author":"Reisizadeh","year":"2020","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3615173"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3558005"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2024.3378205"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/279"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2022.3184770"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3554980"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3558005"},{"key":"ref21","first-page":"942","article-title":"Feature distribution matching for federated domain generalization","volume-title":"Asian Conference on Machine Learning.","author":"Sun","year":"2023"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207469"},{"key":"ref23","first-page":"586","article-title":"An efficient frame-work for clustered federated learning","volume":"33","author":"Ghosh","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/EIECS53707.2021.9588126"},{"key":"ref25","author":"Lin","year":"2020","journal-title":"Real-time edge intelligence in the making: A collaborative learning framework via federated meta-learning"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.02140"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3228893"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3015958"},{"key":"ref29","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"McMahan","year":"2017","journal-title":"PMLR"},{"key":"ref30","author":"Mirza","year":"2014","journal-title":"Conditional generative adversarial nets"},{"key":"ref31","author":"Yan","year":"2023","journal-title":"A simple data augmentation for feature distribution skewed federated learning"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI52829.2022.9761404"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533081"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/FMEC59375.2023.10306055"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.02036"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s00446-007-0022-4"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3343440"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.84.4.327"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-64803-w"},{"key":"ref40","article-title":"Optimizing f-measures by cost-sensitive classification","author":"Parambath","year":"2014","journal-title":"Advances in Neural Information Processing Systems 27"}],"event":{"name":"2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA)","location":"San Diego, CA, USA","start":{"date-parts":[[2024,10,6]]},"end":{"date-parts":[[2024,10,10]]}},"container-title":["2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10722027\/10722766\/10722828.pdf?arnumber=10722828","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T02:27:50Z","timestamp":1732674470000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10722828\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,6]]},"references-count":40,"URL":"https:\/\/doi.org\/10.1109\/dsaa61799.2024.10722828","relation":{},"subject":[],"published":{"date-parts":[[2024,10,6]]}}}