{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T15:44:09Z","timestamp":1782834249117,"version":"3.54.5"},"reference-count":46,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62272418"],"award-info":[{"award-number":["62272418"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62202080"],"award-info":[{"award-number":["62202080"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2023M733354"],"award-info":[{"award-number":["2023M733354"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Project of Liaoning Province","award":["2023JH1\/10400083"],"award-info":[{"award-number":["2023JH1\/10400083"]}]},{"name":"Dalian Science and Technology Talent Innovation Support Plan for Outstanding Young Scholars","award":["2023RY023"],"award-info":[{"award-number":["2023RY023"]}]},{"name":"Xiaomi Young Talents Program"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Mobile Comput."],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1109\/tmc.2025.3563265","type":"journal-article","created":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T13:43:39Z","timestamp":1745329419000},"page":"9709-9725","source":"Crossref","is-referenced-by-count":6,"title":["Federated Unlearning With Fast Recovery"],"prefix":"10.1109","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0129-2231","authenticated-orcid":false,"given":"Changjun","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8349-0396","authenticated-orcid":false,"given":"Chenglin","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6547-3472","authenticated-orcid":false,"given":"Minglu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0906-4217","authenticated-orcid":false,"given":"Pengfei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Dalian University of Technology, Dalian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3124599"},{"key":"ref2","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref3","article-title":"Federated collaborative filtering for privacy-preserving personalized recommendation system","author":"Ammad-Ud-Din","year":"2019"},{"key":"ref4","article-title":"FADL: Federated-autonomous deep learning for distributed electronic health record","author":"Liu","year":"2018"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2022.3213314"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-57959-7"},{"key":"ref7","article-title":"The California Consumer Privacy Act: Towards a European -style privacy regime in the United States","volume":"23","author":"Pardau","year":"2018","journal-title":"J. Technol. Law Policy"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.004.2300056"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM48880.2022.9796721"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1017\/9781108966559.019"},{"key":"ref11","article-title":"Federated unlearning: How to efficiently erase a client in FL?","author":"Halimi","year":"2022"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583305"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570463"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/954339.954342"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2015.35"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3266233"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20083-0_6"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00750"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/SP40001.2021.00019"},{"key":"ref20","article-title":"SoK: Challenges and opportunities in federated unlearning","author":"Jeong","year":"2024"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2024.3355188"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2023.3343117"},{"key":"ref23","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"ref24","article-title":"Efficient lifelong learning with a-gem","author":"Chaudhry","year":"2018"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.587"},{"key":"ref26","first-page":"6470","article-title":"Gradient episodic memory for continual learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lopez-Paz"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00810"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.753"},{"key":"ref29","first-page":"13677","article-title":"Compacting, picking and growing for unforgetting continual learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Hung"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611835114"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/137"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i9.16952"},{"key":"ref33","first-page":"19111","article-title":"HRN: A holistic approach to one class learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Hu"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2773081"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref36","article-title":"Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms","author":"Xiao","year":"2017"},{"issue":"4","key":"ref37","article-title":"Learning multiple layers of features from tiny images","volume-title":"Handbook of Systemic Autoimmune Diseases","volume":"1","author":"Krizhevsky","year":"2009"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3321594"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512222"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2025.113353"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5895"},{"key":"ref43","first-page":"26311","article-title":"Federated learning with label distribution skew via logits calibration","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zhang"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2023.3345388"}],"container-title":["IEEE Transactions on Mobile Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7755\/11154819\/10972332.pdf?arnumber=10972332","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T19:54:13Z","timestamp":1757534053000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10972332\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":46,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tmc.2025.3563265","relation":{},"ISSN":["1536-1233","1558-0660","2161-9875"],"issn-type":[{"value":"1536-1233","type":"print"},{"value":"1558-0660","type":"electronic"},{"value":"2161-9875","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10]]}}}