{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,10]],"date-time":"2025-05-10T07:10:08Z","timestamp":1746861008971,"version":"3.40.5"},"reference-count":21,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T00:00:00Z","timestamp":1742774400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T00:00:00Z","timestamp":1742774400000},"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":["62372050"],"award-info":[{"award-number":["62372050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,3,24]]},"DOI":"10.1109\/wcnc61545.2025.10978255","type":"proceedings-article","created":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T17:53:33Z","timestamp":1746813213000},"page":"01-06","source":"Crossref","is-referenced-by-count":0,"title":["PGPFL: A Parameter Guard-Based Efficient Personalized Federated Learning Framework with Local Differential Privacy"],"prefix":"10.1109","author":[{"given":"Zhipeng","family":"Gao","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications"}]},{"given":"Leyu","family":"Han","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications"}]},{"given":"Qian","family":"Luo","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications"}]},{"given":"Ze","family":"Chai","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1109\/MSP.2020.2975749"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1609\/aaai.v37i9.26330"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1109\/TCOMM.2023.3288591"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/TSC.2024.3382958"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/OJCS.2023.3260732"},{"key":"ref6","article-title":"Think locally, act globally: Federated learning with local and global representations","author":"Pu Liang","year":"2020","journal-title":"arXiv preprint"},{"key":"ref7","article-title":"Federated learning with personalization layers","author":"Arivazhagan","year":"2019","journal-title":"arXiv preprint"},{"key":"ref8","article-title":"Personalized federated learning: A meta-learning approach","author":"Fallah","year":"2020","journal-title":"arXiv preprint"},{"key":"ref9","first-page":"10092","article-title":"Parameterized knowledge transfer for personalized federated learning","volume":"34","author":"Zhang","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref10","first-page":"12878","article-title":"Data-free knowledge distillation for heterogeneous federated learning","volume-title":"International conference on machine learning","author":"Zhu","year":"2021"},{"key":"ref11","article-title":"Federated learning of a mixture of global and local models","author":"Hanzely","year":"2020","journal-title":"arXiv preprint"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1145\/3133956.3134077"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1145\/3369583.3392686"},{"key":"ref14","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":"ref15","article-title":"Adaptive personalized federated learning","author":"Deng","year":"2020","journal-title":"arXiv p rep rint"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1609\/aaai.v36i8.20819"},{"key":"ref17","article-title":"On bridging generic and personalized federated learning for image classification","author":"Chen","year":"2021","journal-title":"arXiv preprint"},{"key":"ref18","article-title":"Fedbn: Federated learning on non-iid features via local batch normalization","author":"Li","year":"2021","journal-title":"arXiv preprint"},{"key":"ref19","first-page":"3987","article-title":"Continual learning through synaptic intelligence","volume-title":"International Conference on Machine Learning","author":"Zenke","year":"2017"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.24963\/ijcai.2021\/217"},{"key":"ref21","article-title":"Fedbabu: Towards enhanced representation for federated image classification","author":"Oh","year":"2021","journal-title":"arXiv preprint"}],"event":{"name":"2025 IEEE Wireless Communications and Networking Conference (WCNC)","start":{"date-parts":[[2025,3,24]]},"location":"Milan, Italy","end":{"date-parts":[[2025,3,27]]}},"container-title":["2025 IEEE Wireless Communications and Networking Conference (WCNC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10978109\/10978116\/10978255.pdf?arnumber=10978255","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,10]],"date-time":"2025-05-10T06:33:45Z","timestamp":1746858825000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10978255\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,24]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/wcnc61545.2025.10978255","relation":{},"subject":[],"published":{"date-parts":[[2025,3,24]]}}}