{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T08:25:11Z","timestamp":1767860711352,"version":"3.49.0"},"reference-count":41,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"24","license":[{"start":{"date-parts":[[2019,12,15]],"date-time":"2019-12-15T00:00:00Z","timestamp":1576368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,12,15]],"date-time":"2019-12-15T00:00:00Z","timestamp":1576368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,12,15]],"date-time":"2019-12-15T00:00:00Z","timestamp":1576368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100010663","name":"H2020 European Research Council","doi-asserted-by":"publisher","award":["677854"],"award-info":[{"award-number":["677854"]}],"id":[{"id":"10.13039\/100010663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Signal Process."],"published-print":{"date-parts":[[2019,12,15]]},"DOI":"10.1109\/tsp.2019.2952051","type":"journal-article","created":{"date-parts":[[2019,11,6]],"date-time":"2019-11-06T20:49:43Z","timestamp":1573073383000},"page":"6270-6284","source":"Crossref","is-referenced-by-count":55,"title":["Computation Scheduling for Distributed Machine Learning With Straggling Workers"],"prefix":"10.1109","volume":"67","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7343-6628","authenticated-orcid":false,"given":"Mohammad Mohammadi","family":"Amiri","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7725-395X","authenticated-orcid":false,"given":"Deniz","family":"Gunduz","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","article-title":"Deep gradient compression: Reducing the communication bandwidth for distributed training","author":"lin","year":"2018","journal-title":"arXiv 1712 01887"},{"key":"ref38","article-title":"AdaComp: Adaptive residual gradient compression for data-parallel distributed training","author":"chen","year":"2017","journal-title":"arXiv 1712 02679v1"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2014.7028591"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2851241"},{"key":"ref31","first-page":"401","article-title":"Prioritized task scheduling in fog computing","author":"choudhari","year":"0","journal-title":"Proc 34 Annual ACM Southeast Conf"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.22266\/ijies2018.0630.26"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8852172"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1045"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-0000(75)80008-0"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2019.2919553"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2017.8262882"},{"key":"ref40","article-title":"eSGD: Communication efficient distributed deep learning on the edge","author":"tao","year":"0","journal-title":"Proc Workshop Hot Topics Edge Comput"},{"key":"ref11","article-title":"Polynomial codes: An optimal design for high-dimensional coded matrix multiplication","author":"yu","year":"2018","journal-title":"arXiv 1705 10464"},{"key":"ref12","article-title":"Lagrange coded computing: Optimal design for resiliency, security and privacy","author":"yu","year":"2018","journal-title":"arXiv 1806 00939"},{"key":"ref13","article-title":"Polynomially coded regression: Optimal straggler mitigation via data encoding","author":"li","year":"2018","journal-title":"arXiv 1805 09934v1"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2018.8437473"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682911"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPSW.2018.00137"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2018.8437871"},{"key":"ref18","article-title":"Rateless codes for near-perfect load balancing in distributed matrix-vector multiplication","author":"mallick","year":"2018","journal-title":"arXiv 1804 10332"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2019.8849684"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.4304\/jsw.9.2.466-473"},{"key":"ref4","first-page":"3368","article-title":"Gradient coding: Avoiding stragglers in distributed learning","author":"tandon","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/1478873.1478901"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2017.2736066"},{"key":"ref6","article-title":"Slow and stale gradients can win the race: Error-runtime trade-offs in distributed SGD","author":"dutta","year":"2018","journal-title":"arXiv 1803 01113v3"},{"key":"ref29","first-page":"3821","article-title":"Improved PSO-based task scheduling algorithm in cloud computing","volume":"9","author":"zhan","year":"2012","journal-title":"J Inf Comput Sci"},{"key":"ref5","article-title":"Improving distributed gradient descent using Reed-Solomon codes","author":"halbawi","year":"2017","journal-title":"arXiv 1706 05436"},{"key":"ref8","article-title":"Communication-computation efficient gradient coding","author":"ye","year":"2018","journal-title":"arXiv 1802 03475v1"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2019.8849514"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.4330060702"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2018.8437563"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2019.8849334"},{"key":"ref22","article-title":"Collaborative machine learning at the wireless edge with blind transmitters","author":"amiri","year":"0","journal-title":"Proc IEEE Global Conf Signal Inf Process"},{"key":"ref21","article-title":"Federated learning over wireless fading channels","author":"amiri","year":"2019","journal-title":"arXiv 1907 09769"},{"key":"ref24","first-page":"1058","article-title":"1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs","author":"seide1","year":"0","journal-title":"Proc INTERSPEECH"},{"key":"ref41","first-page":"9872","article-title":"ATOMO: Communication-efficient learning via atomic sparsification","author":"wang","year":"0","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref23","article-title":"Federated learning: Strategies for improving communication efficiency","author":"konecny","year":"2017","journal-title":"arXiv 1610 05492"},{"key":"ref26","article-title":"Combating computational heterogeneity in large-scale distributed computing via work exchange","author":"attia","year":"2017","journal-title":"arXiv 1711 08452"},{"key":"ref25","first-page":"1488","article-title":"Scalable distributed DNN training using commodity GPU cloud computing","author":"strom","year":"0","journal-title":"Proc INTERSPEECH"}],"container-title":["IEEE Transactions on Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/78\/8930150\/08892615.pdf?arnumber=8892615","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:44:59Z","timestamp":1657745099000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8892615\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,15]]},"references-count":41,"journal-issue":{"issue":"24"},"URL":"https:\/\/doi.org\/10.1109\/tsp.2019.2952051","relation":{},"ISSN":["1053-587X","1941-0476"],"issn-type":[{"value":"1053-587X","type":"print"},{"value":"1941-0476","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,12,15]]}}}