{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T03:08:48Z","timestamp":1770347328550,"version":"3.49.0"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"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\/ACM Trans. Networking"],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1109\/tnet.2022.3231864","type":"journal-article","created":{"date-parts":[[2023,1,2]],"date-time":"2023-01-02T18:55:41Z","timestamp":1672685741000},"page":"2499-2514","source":"Crossref","is-referenced-by-count":21,"title":["SlimFL: Federated Learning With Superposition Coding Over Slimmable Neural Networks"],"prefix":"10.1109","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0405-8843","authenticated-orcid":false,"given":"Won Joon","family":"Yun","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Korea University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunseok","family":"Kwak","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Korea University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hankyul","family":"Baek","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Korea University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8435-0646","authenticated-orcid":false,"given":"Soyi","family":"Jung","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Ajou University, Suwon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7970-2245","authenticated-orcid":false,"given":"Mingyue","family":"Ji","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, The University of Utah, Salt Lake City, UT, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0261-0171","authenticated-orcid":false,"given":"Mehdi","family":"Bennis","sequence":"additional","affiliation":[{"name":"Centre for Wireless Communications, University of Oulu, Oulu, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7623-6552","authenticated-orcid":false,"given":"Jihong","family":"Park","sequence":"additional","affiliation":[{"name":"School of Information Technology, Deakin University, Geelong, VIC, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2126-768X","authenticated-orcid":false,"given":"Joongheon","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Korea University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM48880.2022.9796733"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.001.2000200"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JSYST.2020.3019035"},{"key":"ref4","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Int. Conf. Artif. Intell. Statist. (AISTATS)","author":"McMahan"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737464"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2020.3035770"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2988033"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1972.1054727"},{"key":"ref9","article-title":"Federated learning: Collaborative machine learning without centralized training data","author":"McMahan","year":"2017","journal-title":"Google AI Blog"},{"key":"ref10","first-page":"1","article-title":"FedBN: Federated learning on non-IID features via local batch normalization","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Li"},{"key":"ref11","first-page":"429","article-title":"Federated optimization in heterogeneous networks","volume-title":"Proc. Mach. Learn. Syst.","volume":"2","author":"Li"},{"key":"ref12","first-page":"1","article-title":"Adaptive federated optimization","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Reddi"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3037554"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3024629"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2020.2978824"},{"key":"ref16","first-page":"1","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Han"},{"key":"ref17","first-page":"1","article-title":"Distilling the knowledge in a neural network","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","author":"Hinton"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8851874"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013812"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00189"},{"key":"ref21","first-page":"1","article-title":"Slimmable neural networks","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Yu"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00850"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1587\/transcom.E98.B.403"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2015.2394393"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2016.2518165"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2017.1500657CM"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3064995"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511807213"},{"key":"ref29","article-title":"A survey of quantization methods for efficient neural network inference","author":"Gholami","year":"2021","journal-title":"arXiv:2103.13630"},{"key":"ref30","volume-title":"Wireless Communications","author":"Molisch","year":"2011"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2017.2720176"},{"key":"ref32","first-page":"1","article-title":"Federated learning with matched averaging","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Wang"},{"key":"ref33","first-page":"1","article-title":"On the convergence of FedAvg on non-IID data","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Li"},{"key":"ref34","first-page":"4519","article-title":"Tighter theory for local SGD on identical and heterogeneous data","volume-title":"Proc. Int. Conf. Artif. Intell. Statist. (AISTATS)","author":"Khaled"},{"key":"ref35","first-page":"1","article-title":"Local SGD converges fast and communicates little","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Stich"},{"key":"ref36","first-page":"1","article-title":"Simultaneous training of partially masked neural networks","volume-title":"Proc. Int. Conf. Artif. Intell. Statist. (AISTATS)","author":"Mohtashami"},{"key":"ref37","article-title":"Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms","author":"Xiao","year":"2017","journal-title":"arXiv:1708.07747"},{"key":"ref38","first-page":"1","article-title":"Measuring the effects of non-identical data distribution for federated visual classification","volume-title":"Proc. Conf. Neural Inf. Process. Syst. (NIPS) Federated Learn. Data Privacy Confidentiality Workshop","author":"Harry Hsu"},{"key":"ref39","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv:1704.04861"},{"key":"ref40","article-title":"Measuring the algorithmic efficiency of neural networks","author":"Hernandez","year":"2020","journal-title":"arXiv:2005.04305"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2002.1010620"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/MVT.2020.3018436"},{"key":"ref43","volume-title":"Cifar-10 (Canadian Institute for Advanced Research)","author":"Krizhevsky","year":"2009"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"}],"container-title":["IEEE\/ACM Transactions on Networking"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/90\/10365667\/10004844.pdf?arnumber=10004844","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T00:49:38Z","timestamp":1705020578000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10004844\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12]]},"references-count":44,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tnet.2022.3231864","relation":{},"ISSN":["1063-6692","1558-2566"],"issn-type":[{"value":"1063-6692","type":"print"},{"value":"1558-2566","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12]]}}}