{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T01:55:04Z","timestamp":1772934904566,"version":"3.50.1"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100031478","name":"NextGenerationEU","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100031478","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,8]]},"DOI":"10.1109\/bigdata66926.2025.11402460","type":"proceedings-article","created":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T20:57:57Z","timestamp":1772830677000},"page":"1723-1731","source":"Crossref","is-referenced-by-count":0,"title":["FedSDE: Self-Distillation with Diffusion Enhanced for One-shot Federated Learning"],"prefix":"10.1109","author":[{"given":"Lingyu","family":"Qiu","sequence":"first","affiliation":[{"name":"University of Naples Federico II,Department of Mathematics and Applications &#x201C;R. Caccioppoli&#x201D;,Italy"}]},{"given":"Daniela","family":"Annunziata","sequence":"additional","affiliation":[{"name":"University of Naples Federico II,Department of Mathematics and Applications &#x201C;R. Caccioppoli&#x201D;,Italy"}]},{"given":"Fabio","family":"Giampaolo","sequence":"additional","affiliation":[{"name":"University of Naples Federico II,Department of Mathematics and Applications &#x201C;R. Caccioppoli&#x201D;,Italy"}]},{"given":"Francesco","family":"Piccialli","sequence":"additional","affiliation":[{"name":"University of Naples Federico II,Department of Mathematics and Applications &#x201C;R. Caccioppoli&#x201D;,Italy"}]}],"member":"263","reference":[{"key":"ref1","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":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3095077"},{"key":"ref3","article-title":"Enhancing one-shot federated learning through data and ensemble co-boosting","author":"Dai","year":"2024","journal-title":"arXiv preprint arXiv"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i11.21446"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.52202\/068431-1556"},{"key":"ref6","article-title":"Distilling the know ledge in a neural network","author":"Hinton","year":"2015","journal-title":"arXiv preprint arXiv"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2939502.2939516"},{"key":"ref8","article-title":"One-shot federated learning via synthetic distiller-distillate communication","author":"Zhang","year":"2024","journal-title":"arXiv preprint arXiv"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/WACV61041.2025.00258"},{"key":"ref10","article-title":"Revisiting self-distillation","author":"Pham","year":"2022","journal-title":"arXiv preprint arXiv"},{"key":"ref11","article-title":"Data-free one-shot federated learning under very high statistical heterogeneity","volume-title":"The Eleventh International Conference on Learning Representations","author":"Heinbaugh"},{"key":"ref12","article-title":"Towards addressing label skews in one-shot federated learning","volume-title":"The Eleventh International Conference on Learning Representations","author":"Diao"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i15.29568"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.04.035"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN54540.2023.10191879"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/wacv61041.2025.00258"},{"key":"ref17","article-title":"Xor mixup: Privacy-preserving data augmentation for one-shot federated learning","author":"Shin","year":"2020","journal-title":"arXiv preprint arXiv"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747113"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI59109.2023.00024"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/electronics13101815"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.52202\/079017-2188"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/443"},{"key":"ref23","article-title":"Towards understanding ensemble, knowledge distillation and self-distillation in deep learning","volume-title":"The Eleventh International Conference on Learning Representations","author":"Allen-Zhu"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011190"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2022.3225185"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s00530-025-01719-3"},{"key":"ref27","first-page":"8780","article-title":"Diffusion models beat gans on image synthesis","volume":"34","author":"Dhariwal","year":"2021","journal-title":"Advances in neural information processing systems"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2025\/1174"},{"key":"ref29","volume-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"issue":"7","key":"ref30","first-page":"3","article-title":"Tiny imagenet visual recognition challenge","volume":"7","author":"Le","year":"2015","journal-title":"CS 231N"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref33","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"33","author":"Ho","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref35","article-title":"Fedcm: Federated learning with client-level momentum","author":"Xu","year":"2021","journal-title":"arXiv preprint arXiv"},{"key":"ref36","article-title":"Fedspeed: Larger local interval, less communication round, and higher generalization accuracy","author":"Sun","year":"2023","journal-title":"arXiv preprint arXiv"},{"key":"ref37","first-page":"32991","article-title":"Dynamic regularized sharpness aware minimization in federated learning: Approaching global consistency and smooth landscape","volume-title":"International conference on machine learning","author":"Sun"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3304453"}],"event":{"name":"2025 IEEE International Conference on Big Data (BigData)","location":"Macau, China","start":{"date-parts":[[2025,12,8]]},"end":{"date-parts":[[2025,12,11]]}},"container-title":["2025 IEEE International Conference on Big Data (BigData)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11400704\/11400712\/11402460.pdf?arnumber=11402460","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T07:19:58Z","timestamp":1772867998000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11402460\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,8]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/bigdata66926.2025.11402460","relation":{},"subject":[],"published":{"date-parts":[[2025,12,8]]}}}