{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T07:11:15Z","timestamp":1761894675934,"version":"build-2065373602"},"reference-count":34,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/icme59968.2025.11209954","type":"proceedings-article","created":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T17:57:42Z","timestamp":1761847062000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["Long-Tailed Federated Learning with Fixed Classifier"],"prefix":"10.1109","author":[{"given":"Yi","family":"Li","sequence":"first","affiliation":[{"name":"Dalian University of Technology,School of Future Technology\/School of Artificial Inteligence,Dalian,China"}]},{"given":"Weichao","family":"Li","sequence":"additional","affiliation":[{"name":"Dalian University of Technology,School of Information and Communication Engineering,Dalian,China"}]},{"given":"Xin","family":"Zheng","sequence":"additional","affiliation":[{"name":"Griffith University,School of Information and Communication Technology,Gold Coast,Australia"}]},{"given":"Haiyan","family":"Fu","sequence":"additional","affiliation":[{"name":"Dalian University of Technology,School of Information and Communication Engineering,Dalian,China"}]},{"given":"Yanqing","family":"Guo","sequence":"additional","affiliation":[{"name":"Dalian University of Technology,School of Future Technology\/School of Artificial Inteligence,Dalian,China"}]}],"member":"263","reference":[{"article-title":"Federated learning with non-iid data","year":"2018","author":"Zhao","key":"ref1"},{"key":"ref2","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"McMahan","year":"2017","journal-title":"Artificial intelligence and statistics"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3268118"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/IPSN54338.2022.00029"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2022.05.003"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3184309"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9412599"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3325366"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00490"},{"key":"ref10","first-page":"21554","article-title":"Robust federated learning: The case of affine distribution shifts","volume":"33","author":"Reisizadeh","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref11","first-page":"10533","article-title":"Dres-fl: Dropout-resilient secure federated learning for non-iid clients via secret data sharing","volume":"35","author":"Shao","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref12","first-page":"35684","article-title":"Factorized-fl: Personalized federated learning with parameter factorization & similarity matching","volume":"35","author":"Jeong","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref13","first-page":"15660","article-title":"One-pass distribution sketch for measuring data heterogeneity in federated learning","volume":"36","author":"Liu","year":"2023","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref14","first-page":"2074","article-title":"Navigating data heterogeneity in federated learning: A semi-supervised federated object detection","volume-title":"Advances in Neural Information Processing Systems","volume":"36","author":"Kim","year":"2023"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2015509117"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/S1063-5203(03)00023-X"},{"article-title":"Long-tail learning via logit adjustment","year":"2020","author":"Menon","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00585"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00855"},{"key":"ref20","first-page":"37991","article-title":"Inducing neural collapse in imbalanced learning: Do we really need a learnable classifier at the end of deep neural network?","volume":"35","author":"Yang","year":"2022","journal-title":"Advances in neural information processing systems"},{"key":"ref21","first-page":"27542","article-title":"Feature directions matter: Long-tailed learning via rotated balanced representation","volume-title":"International Conference on Machine Learning","author":"Peifeng"},{"key":"ref22","first-page":"3794","article-title":"Cheap orthogonal constraints in neural networks: A simple parametrization of the orthogonal and unitary group","volume-title":"International Conference on Machine Learning","author":"Lezcano-Casado"},{"key":"ref23","first-page":"4175","article-title":"Balanced meta-softmax for long-tailed visual recognition","volume":"33","author":"Ren","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i13.29416"},{"author":"Hsu","key":"ref25","article-title":"Measuring the effects of non-identical data distribution for federated visual classification. arxiv 2019"},{"key":"ref26","first-page":"429","article-title":"Federated optimization in heterogeneous networks","volume-title":"Proceedings of Machine learning and systems","volume":"2","author":"Li"},{"key":"ref27","first-page":"2351","article-title":"Ensemble distillation for robust model fusion in federated learning","volume":"33","author":"Lin","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00949"},{"key":"ref29","first-page":"5972","article-title":"No fear of heterogeneity: Classifier calibration for federated learning with non-iid data","author":"Luo","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref30","first-page":"7611","article-title":"Tackling the objective inconsistency problem in heterogeneous federated optimization","author":"Wang","year":"2020","journal-title":"Advances in neural information processing systems"},{"article-title":"Fed-focal loss for imbalanced data classification in federated learning","year":"2020","author":"Sarkar","key":"ref31"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i11.17219"},{"article-title":"Decoupling representation and classifier for long-tailed recognition","year":"2019","author":"Kang","key":"ref33"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/308"}],"event":{"name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","start":{"date-parts":[[2025,6,30]]},"location":"Nantes, France","end":{"date-parts":[[2025,7,4]]}},"container-title":["2025 IEEE International Conference on Multimedia and Expo (ICME)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11208895\/11208897\/11209954.pdf?arnumber=11209954","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T05:33:12Z","timestamp":1761888792000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11209954\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/icme59968.2025.11209954","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}