{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T19:52:33Z","timestamp":1782762753279,"version":"3.54.5"},"reference-count":38,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"13","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"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":["IEEE Internet Things J."],"published-print":{"date-parts":[[2026,7,1]]},"DOI":"10.1109\/jiot.2026.3687140","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T19:49:18Z","timestamp":1777405758000},"page":"29929-29940","source":"Crossref","is-referenced-by-count":0,"title":["CEHGLS: A Communication-Efficient Head Gradient Linear Search for Personalized Federated Learning Under Data Heterogeneity"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-8139-4081","authenticated-orcid":false,"given":"Zouquan","family":"Chen","sequence":"first","affiliation":[{"name":"College of Information Science and Technology, Shihezi University, Shihezi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3150-2986","authenticated-orcid":false,"given":"Lidong","family":"Zheng","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8488-1559","authenticated-orcid":false,"given":"Xiaofang","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Shihezi University, Shihezi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3093-6929","authenticated-orcid":false,"given":"Yuchen","family":"Zheng","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Shihezi University, Shihezi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"5289","article-title":"FBLG: A local graph based approach for handling dual skewed non-IID data in federated learning","volume-title":"Proc. Int. Joint Conf. Artif. Intell.","author":"Xu"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICPADS56603.2022.00107"},{"key":"ref3","first-page":"4136","article-title":"Feature norm regularized federated learning: Utilizing data disparities for model performance gains","volume-title":"Proc. Int. Joint Conf. Artif. Intell.","author":"Hu"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00077"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2022.05.003"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599345"},{"key":"ref7","first-page":"1","article-title":"FedBABU: Towards enhanced representation for federated image classification","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Oh"},{"key":"ref8","first-page":"5132","article-title":"SCAFFOLD: Stochastic controlled averaging for federated learning","volume-title":"Proc. 37th Int. Conf. Mach. Learn.","volume":"119","author":"Karimireddy"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i2.20095"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2024\/526"},{"key":"ref11","first-page":"493","article-title":"BatchCrypt: Efficient homomorphic encryption for cross-silo federated learning","volume-title":"Proc. USENIX Annu. Tech. Conf.","author":"Zhang"},{"key":"ref12","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. 20th Int. Conf. Artif. Intell. Statist.","volume":"54","author":"McMahan"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3349323"},{"key":"ref14","first-page":"429","article-title":"Federated optimization in heterogeneous networks","volume":"2","author":"Li","year":"2020","journal-title":"Mach. Learn. Syst."},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01057"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2025.3636225"},{"key":"ref17","first-page":"38461","article-title":"Preservation of the global knowledge by not-true distillation in federated learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Bae"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.2022.2157882"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2024\/594"},{"key":"ref20","article-title":"Federated learning based on dynamic regularization","author":"Acar","year":"2021","journal-title":"arXiv:2111.04263"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3449129"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00983"},{"key":"ref23","article-title":"Federated learning with personalization layers","author":"Arivazhagan","year":"2019","journal-title":"arXiv:1912.00818"},{"key":"ref24","first-page":"2089","article-title":"Exploiting shared representations for personalized federated learning","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","author":"Collins"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2025.108038"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.02854"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2025.3630329"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3124599"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2024.3515793"},{"key":"ref30","article-title":"FLASHE: Additively symmetric homomorphic encryption for cross-silo federated learning","author":"Jiang","year":"2021","journal-title":"arXiv:2109.00675"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3390\/fi13040094"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2022.3219485"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.12"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.02398"},{"key":"ref35","article-title":"FedMix: Approximation of mixup under mean augmented federated learning","author":"Yoon","year":"2021","journal-title":"arXiv:2107.00233"},{"key":"ref36","first-page":"1","article-title":"Internal cross-layer gradients for extending homogeneity to heterogeneity in federated learning","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Chan"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20819"},{"issue":"50","key":"ref38","first-page":"1","article-title":"PFLlib: A beginner-friendly and comprehensive personalized federated learning library and benchmark","volume":"26","author":"Zhang","year":"2025","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488907\/11581326\/11494774.pdf?arnumber=11494774","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T19:41:46Z","timestamp":1782762106000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11494774\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,1]]},"references-count":38,"journal-issue":{"issue":"13"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2026.3687140","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,1]]}}}