{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:59:06Z","timestamp":1783439946862,"version":"3.54.6"},"reference-count":31,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Hong Kong Research Grants Council","award":["17208319"],"award-info":[{"award-number":["17208319"]}]},{"name":"Hong Kong Research Grants Council","award":["17209917"],"award-info":[{"award-number":["17209917"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Signal Process."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/tsp.2020.2983166","type":"journal-article","created":{"date-parts":[[2020,3,31]],"date-time":"2020-03-31T03:12:55Z","timestamp":1585624375000},"page":"2128-2142","source":"Crossref","is-referenced-by-count":102,"title":["High-Dimensional Stochastic Gradient Quantization for Communication-Efficient Edge Learning"],"prefix":"10.1109","volume":"68","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9147-656X","authenticated-orcid":false,"given":"Yuqing","family":"Du","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0643-0445","authenticated-orcid":false,"given":"Sheng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8773-4629","authenticated-orcid":false,"given":"Kaibin","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref31","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1080\/00031305.1992.10475864","article-title":"Distributional identities of beta and chi-squared variates: A geometrical interpretation","volume":"46","author":"bailey","year":"1992","journal-title":"Amer Statistician"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2007.915691"},{"key":"ref10","first-page":"559","article-title":"signSGD: Compressed optimisation for non-convex problems","volume":"80","author":"bernstein","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref11","first-page":"5321","article-title":"Error compensated quantized SGD and its applications to large-scale distributed optimization","author":"wu","year":"0","journal-title":"Proc IEEE Intern Conf on Machine Learning"},{"key":"ref12","article-title":"Communication-efficient distributed blockwise momentum SGD with error-feedback","author":"zheng","year":"2019"},{"key":"ref13","article-title":"ADAM: A method for stochastic optimization","author":"kingma","year":"2014"},{"key":"ref14","volume":"159","author":"gersho","year":"2012","journal-title":"Vector Quantization and Signal Compression"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2008.081002"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2003.817433"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2003.817466"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2007.070804"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2011.022811.090744"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2003.822171"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2019.8849334"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1080\/10586458.2008.10129018"},{"key":"ref3","article-title":"Federated learning: Strategies for improving communication efficiency","author":"kone?ny","year":"2016"},{"key":"ref6","first-page":"3368","article-title":"Gradient coding: Avoiding stragglers in distributed learning","author":"tandon","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref29","volume":"290","author":"conway","year":"2013","journal-title":"Sphere Packings Lattices and Groups"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref8","article-title":"vqSGD: Vector quantized stochastic gradient descent","author":"gandikota","year":"2019"},{"key":"ref7","first-page":"4035","article-title":"ZIPML: Training linear models with end-to-end low precision, and a little bit of deep learning","author":"zhang","year":"0","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref2","article-title":"Towards an intelligent edge: Wireless communication meets machine learning","author":"zhu","year":"2018"},{"key":"ref9","first-page":"1709","article-title":"QSGD: Communication-efficient SGD via gradient quantization and encoding","author":"alistarh","year":"0","journal-title":"Proc Adv Neu Inf Proc Sys"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2019.2941458"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2009.2014272"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CISS.2012.6310934"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"1853","DOI":"10.1109\/TSP.2006.871967","article-title":"Design and analysis of transmit-beamforming based on limited-rate feedback","volume":"54","author":"xia","year":"2006","journal-title":"IEEE Trans Sig Process"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/JCN.2016.000012"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2013.111413.130379"},{"key":"ref26","article-title":"Directional analysis of stochastic gradient descent via von mises-fisher distributions in deep learning","author":"lee","year":"2018"},{"key":"ref25","first-page":"337","article-title":"A procedure to find exact critical values of kolmogorov-smirnov test","volume":"21","author":"facchinetti","year":"2009","journal-title":"Statistica Applicata"}],"container-title":["IEEE Transactions on Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/78\/8933520\/09050465.pdf?arnumber=9050465","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,3]],"date-time":"2024-08-03T03:24:19Z","timestamp":1722655459000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9050465\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/tsp.2020.2983166","relation":{},"ISSN":["1053-587X","1941-0476"],"issn-type":[{"value":"1053-587X","type":"print"},{"value":"1941-0476","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}