{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T16:08:29Z","timestamp":1770739709059,"version":"3.49.0"},"reference-count":41,"publisher":"Tsinghua University Press","issue":"2","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62372472"],"award-info":[{"award-number":["62372472"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2024JJ4068"],"award-info":[{"award-number":["2024JJ4068"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Big Data Min. Anal."],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.26599\/bdma.2025.9020068","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T20:52:42Z","timestamp":1770411162000},"page":"481-499","source":"Crossref","is-referenced-by-count":0,"title":["CEFCIL: Comprehensive Ensemble Framework for Exemplar-Free Class Incremental Learning"],"prefix":"10.26599","volume":"9","author":[{"given":"Weike","family":"Liu","sequence":"first","affiliation":[{"name":"National Key Laboratory of Information Systems Engineering and College of Systems Engineering, National University of Defense Technology,Changsha,China,410003"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng","family":"Zhu","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Information Systems Engineering and College of Systems Engineering, National University of Defense Technology,Changsha,China,410003"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University,Changsha,China,410083"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lailong","family":"Luo","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Information Systems Engineering and College of Systems Engineering, National University of Defense Technology,Changsha,China,410003"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaoyun","family":"Ding","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Information Systems Engineering and College of Systems Engineering, National University of Defense Technology,Changsha,China,410003"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingbao","family":"Liu","sequence":"additional","affiliation":[{"name":"National University of Defense Technology,Laboratory for Big Data and Decision,Changsha,China,410003"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"11138","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.26599\/BDMA.2018.9020001"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2773081"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.587"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3057446"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.26599\/BDMA.2023.9020006"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01258-8_15"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58565-5_6"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00092"},{"key":"ref10","article-title":"Divide and not forget: Ensemble of selectively trained experts in continual learning","author":"Rype\u015b\u0107","year":"2024","journal-title":"arXiv preprint"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00581"},{"key":"ref12","first-page":"1096","article-title":"Class-incremental learning via dual augmentation","volume-title":"Proc. 35th Int. Conf. Neural Information Processing Systems","author":"Zhu","year":"2021"},{"key":"ref13","first-page":"288","article-title":"FeCAM:Exploiting the heterogeneity of class distributions in exemplar-free continual learning","volume-title":"Proc. 37th Int. Conf. Neural Information Processing Systems","author":"Goswami"},{"key":"ref14","first-page":"843","article-title":"ACIL: Analytic class-incremental learning with absolute memorization and privacy protection","volume-title":"Proc. 36th Int. Conf. Neural Information Processing Systems","author":"Zhuang"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00748"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i15.29670"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00908"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19809-0_15"},{"key":"ref19","article-title":"Understanding dimensional collapse in contrastive self-supervised learning","author":"Jing","year":"2021","journal-title":"arXiv preprint"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01622"},{"key":"ref21","article-title":"Towards understanding and mitigating dimensional collapse in heterogeneous federated learning","author":"Shi","year":"2022","journal-title":"arXiv preprint"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.83"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00701"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.202"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.180"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/wacv56688.2023.00390"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-021-10570-2"},{"key":"ref28","first-page":"321","article-title":"Pseudoinverse learning algorithm for feedforward neural networks","volume-title":"Proc. Int. Conf. Neural Networks and Applications","author":"Guo"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611835114"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01322"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3429383"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.4140\/TCP.n.2015.249"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/BF00058655"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.753"},{"key":"ref35","article-title":"GDC-generalized distribution calibration for few-shot learning","author":"Kumar","year":"2022","journal-title":"arXiv preprint"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00398"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33709-3_35"},{"key":"ref38","volume-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/iccv.2019.00149"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-022-3600-y"}],"container-title":["Big Data Mining and Analytics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8254253\/11373433\/11373435.pdf?arnumber=11373435","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T21:10:15Z","timestamp":1770671415000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11373435\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":41,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.26599\/bdma.2025.9020068","relation":{},"ISSN":["2096-0654","2097-406X"],"issn-type":[{"value":"2096-0654","type":"print"},{"value":"2097-406X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]}}}