{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T16:14:32Z","timestamp":1782836072421,"version":"3.54.5"},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T00:00:00Z","timestamp":1651449600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T00:00:00Z","timestamp":1651449600000},"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":[],"published-print":{"date-parts":[[2022,5,2]]},"DOI":"10.1109\/infocom48880.2022.9796733","type":"proceedings-article","created":{"date-parts":[[2022,6,20]],"date-time":"2022-06-20T21:18:49Z","timestamp":1655759929000},"page":"1729-1738","source":"Crossref","is-referenced-by-count":21,"title":["Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks"],"prefix":"10.1109","author":[{"given":"Hankyul","family":"Baek","sequence":"first","affiliation":[{"name":"Korea University,Department of Electrical and Computer Engineering,Seoul,Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Won Joon","family":"Yun","sequence":"additional","affiliation":[{"name":"Korea University,Department of Electrical and Computer Engineering,Seoul,Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunseok","family":"Kwak","sequence":"additional","affiliation":[{"name":"Korea University,Department of Electrical and Computer Engineering,Seoul,Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soyi","family":"Jung","sequence":"additional","affiliation":[{"name":"Hallym University,School of Software,Chuncheon,Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingyue","family":"Ji","sequence":"additional","affiliation":[{"name":"University of Utah,Department of Electrical and Computer Engineering,Salt Lake City,UT,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mehdi","family":"Bennis","sequence":"additional","affiliation":[{"name":"University of Oulu,Centre for Wireless Communications,Oulu,Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jihong","family":"Park","sequence":"additional","affiliation":[{"name":"Deakin University,School of Information Technology,Geelong,Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joongheon","family":"Kim","sequence":"additional","affiliation":[{"name":"Korea University,Department of Electrical and Computer Engineering,Seoul,Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8851874"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013812"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511807213"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2017.1500657CM"},{"key":"ref14","article-title":"A field guide to federated optimization","author":"wang","year":"2021"},{"key":"ref15","first-page":"4519","article-title":"Tighter theory for local SGD on identical and heterogeneous data","author":"khaled","year":"2020","journal-title":"Proc of International Conference on Artificial Intelligence and Statistics (AISTATS)"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1137\/S0363012993250220"},{"key":"ref17","article-title":"On the convergence of FedAvg on non-iid data","author":"li","year":"2020","journal-title":"Proc of International Conference on Learning Representation (ICLR)"},{"key":"ref18","article-title":"Simultaneous training of partially masked neural networks","author":"mohtashami","year":"2021","journal-title":"arxiv preprint abs\/2106 08895"},{"key":"ref19","article-title":"Slimmable neural networks","author":"yu","year":"2019","journal-title":"Proc of International Conference on Learning Representation (ICLR)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2021.3055679"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2019.2941458"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2007.382406"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00189"},{"key":"ref8","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding","author":"han","year":"2016","journal-title":"Proc of International Conference on Learning Representations (ICLR)"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1972.1054727"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737464"},{"key":"ref1","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"mcmahan","year":"2017","journal-title":"Proc of International Conference on Artificial Intelligence and Statistics (AISTATS)"},{"key":"ref9","first-page":"1","article-title":"Distilling the knowledge in a neural network","author":"hinton","year":"2015","journal-title":"Proc of the Conference on Neural Information Processing Systems (NIPS) Deep Learning and Representation Learning Workshop"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2017.2720176"},{"key":"ref22","article-title":"Measuring the effects of non-identical data distribution for federated visual classification","author":"hsu","year":"2019","journal-title":"Conference on Neural Information Processing Systems (NeurIPS) Workshop on Federated Learning for Data Privacy and Confidentiality (available on arXiv preprint abs\/1909 06335)"},{"key":"ref21","article-title":"Local SGD converges fast and communicates little","author":"stich","year":"2018","journal-title":"Proc of International Conference on Learning Representations (ICLR)"},{"key":"ref23","article-title":"Measuring the algorithmic efficiency of neural networks","author":"hernandez","year":"2020"}],"event":{"name":"IEEE INFOCOM 2022 - IEEE Conference on Computer Communications","location":"London, United Kingdom","start":{"date-parts":[[2022,5,2]]},"end":{"date-parts":[[2022,5,5]]}},"container-title":["IEEE INFOCOM 2022 - IEEE Conference on Computer Communications"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9796607\/9796652\/09796733.pdf?arnumber=9796733","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T20:46:37Z","timestamp":1658177197000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9796733\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,2]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/infocom48880.2022.9796733","relation":{},"subject":[],"published":{"date-parts":[[2022,5,2]]}}}