{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T03:07:52Z","timestamp":1784948872282,"version":"3.55.0"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Major Key Project of PCL","award":["PCL2022A03"],"award-info":[{"award-number":["PCL2022A03"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61972441"],"award-info":[{"award-number":["61972441"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017610","name":"Shenzhen Science and Technology Innovation Program","doi-asserted-by":"publisher","award":["RCYX20210609104510007"],"award-info":[{"award-number":["RCYX20210609104510007"]}],"id":[{"id":"10.13039\/501100017610","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017610","name":"Shenzhen Science and Technology Innovation Program","doi-asserted-by":"publisher","award":["JCYJ20200109113427092"],"award-info":[{"award-number":["JCYJ20200109113427092"]}],"id":[{"id":"10.13039\/501100017610","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies","award":["2022B1212010005"],"award-info":[{"award-number":["2022B1212010005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst."],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1109\/tcad.2023.3307459","type":"journal-article","created":{"date-parts":[[2023,8,22]],"date-time":"2023-08-22T17:41:16Z","timestamp":1692726076000},"page":"230-243","source":"Crossref","is-referenced-by-count":22,"title":["FedComp: A Federated Learning Compression Framework for Resource-Constrained Edge Computing Devices"],"prefix":"10.1109","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0358-0533","authenticated-orcid":false,"given":"Donglei","family":"Wu","sequence":"first","affiliation":[{"name":"Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weihao","family":"Yang","sequence":"additional","affiliation":[{"name":"Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoyu","family":"Jin","sequence":"additional","affiliation":[{"name":"Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5104-8301","authenticated-orcid":false,"given":"Xiangyu","family":"Zou","sequence":"additional","affiliation":[{"name":"Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wen","family":"Xia","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies, Harbin Institute of Technology, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Binxing","family":"Fang","sequence":"additional","affiliation":[{"name":"Department of New Networks, Peng Cheng Laboratory, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. PMLR","volume":"54","author":"McMahan"},{"key":"ref2","article-title":"Federated optimization: Distributed machine learning for on-device intelligence","author":"Konecn\u00fd","year":"2016","journal-title":"arXiv:1610.02527"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/960"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/769"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6824"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i08.7021"},{"key":"ref7","first-page":"4424","article-title":"Federated multi-task learning","volume-title":"Proc. NeurIPS","author":"Smith"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/642"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2022.3197491"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2021.3114261"},{"key":"ref11","article-title":"Federated learning: Strategies for improving communication efficiency","author":"Konecn\u00fd","year":"2016","journal-title":"arXiv:1610.05492"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2944481"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-28537-0_17"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1561\/9781680837896"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/GLOBECOM42002.2020.9322527"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-020-00636-3"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3093234"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2021.3110743"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2020.3046665"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2023.3240883"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2022.3213345"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/MLHPC.2016.004"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2015-354"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8852172"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1045"},{"key":"ref26","first-page":"1","article-title":"Deep gradient compression: Reducing the communication bandwidth for distributed training","volume-title":"Proc. ICLR","author":"Lin"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11728"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5706"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.05.137"},{"key":"ref30","first-page":"14236","article-title":"PowerSGD: Practical low-rank gradient compression for distributed optimization","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","volume":"32","author":"Vogels"},{"key":"ref31","first-page":"4452","article-title":"Sparsified SGD with memory","volume-title":"Proc. NeurIPS","author":"Stich"},{"key":"ref32","first-page":"1509","article-title":"TernGrad: Ternary gradients to reduce communication in distributed deep learning","volume-title":"Proc. NIPS","author":"Wen"},{"key":"ref33","first-page":"1709","article-title":"QSGD: Communication-efficient SGD via gradient quantization and encoding","volume-title":"Proc. NeurIPS","author":"Alistarh"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-019-00596-3"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2014-274"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCD53106.2021.00087"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCD53106.2021.00088"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3404397.3404408"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3087262"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM48880.2022.9796982"},{"key":"ref41","first-page":"3252","article-title":"Error feedback fixes SignSGD and other gradient compression schemes","volume-title":"Proc. ICML","volume":"97","author":"Karimireddy"},{"key":"ref42","first-page":"5977","article-title":"The convergence of sparsified gradient methods","volume-title":"Proc. NeurIPS","author":"Alistarh"},{"key":"ref43","first-page":"11446","article-title":"Communication-efficient distributed blockwise momentum SGD with error-feedback","volume-title":"Proc. NeurIPS","author":"Zheng"},{"key":"ref44","first-page":"1","article-title":"Variance-based gradient compression for efficient distributed deep learning","volume-title":"Proc. ICLR","author":"Tsuzuku"},{"key":"ref45","first-page":"21150","article-title":"DeepReduce: A sparse-tensor communication framework for federated deep learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Xu"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.17487\/rfc1951"},{"key":"ref47","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. 3rd Int. Conf. Learn. Represent.","author":"Simonyan"},{"key":"ref48","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2012"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref50","article-title":"Speech commands: A dataset for limited-vocabulary speech recognition","author":"Warden","year":"2018","journal-title":"arXiv:1804.03209"},{"key":"ref51","first-page":"1","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. 3rd Int. Conf. Learn. Represent.","author":"Kingma"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20345"}],"container-title":["IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/43\/10372473\/10226409.pdf?arnumber=10226409","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,12]],"date-time":"2024-12-12T19:14:57Z","timestamp":1734030897000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10226409\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":52,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tcad.2023.3307459","relation":{},"ISSN":["0278-0070","1937-4151"],"issn-type":[{"value":"0278-0070","type":"print"},{"value":"1937-4151","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1]]}}}