{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:11:26Z","timestamp":1772907086371,"version":"3.50.1"},"reference-count":66,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Systems on Nanoscale Information fabriCs (SONIC) which is one of the six SRC STARnet Centers"},{"DOI":"10.13039\/100000185","name":"Defense Advanced Research Projects Agency","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000185","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1350314"],"award-info":[{"award-number":["1350314"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1464336"],"award-info":[{"award-number":["1464336"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1553248"],"award-info":[{"award-number":["1553248"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1763657"],"award-info":[{"award-number":["1763657"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Inform. Theory"],"published-print":{"date-parts":[[2019,10]]},"DOI":"10.1109\/tit.2019.2927558","type":"journal-article","created":{"date-parts":[[2019,7,9]],"date-time":"2019-07-09T20:35:46Z","timestamp":1562704546000},"page":"6171-6193","source":"Crossref","is-referenced-by-count":122,"title":["\u201cShort-Dot\u201d: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products"],"prefix":"10.1109","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6500-2627","authenticated-orcid":false,"given":"Sanghamitra","family":"Dutta","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6786-8785","authenticated-orcid":false,"given":"Viveck","family":"Cadambe","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7651-7776","authenticated-orcid":false,"given":"Pulkit","family":"Grover","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","first-page":"3368","article-title":"Gradient coding: Avoiding stragglers in distributed learning","author":"tandon","year":"2017","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref38","first-page":"1","article-title":"Gradient Coding","author":"tandon","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref33","article-title":"Fundamental limits of coded linear transform","author":"wang","year":"2018","journal-title":"arXiv 1804 09791"},{"key":"ref32","first-page":"5139","article-title":"Coded sparse matrix multiplication","author":"wang","year":"2018","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2018.8437563"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2018.8437852"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2018.8635933"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2018.8437542"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2018.2877391"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682347"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2018.8437459"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2014.2342198"},{"key":"ref61","first-page":"5440","article-title":"Straggler mitigation in distributed optimization through data encoding","author":"karakus","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2018.2869794"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2017.8262882"},{"key":"ref64","article-title":"Fast evaluation and interpolation","author":"kung","year":"1973"},{"key":"ref27","first-page":"1","article-title":"Polynomial codes: An optimal design for high-dimensional coded matrix multiplication","author":"yu","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/BF03167332"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2005.858979"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2019.2929328"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2017.2736066"},{"key":"ref1","first-page":"2092","article-title":"Short-dot: Computing large linear transforms distributedly using coded short dot products","author":"dutta","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/1327452.1327492"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2017.8006963"},{"key":"ref21","first-page":"3","article-title":"Codes for distributed computing: A tutorial","volume":"67","author":"cadambe","year":"2017","journal-title":"IEEE Inf Theory Soc News Lett"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/GLOCOMW.2016.7848828"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2017.8262883"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2017.8006962"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2018.8437549"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2017.2692244"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2017.2756959"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2017.8007058"},{"key":"ref58","first-page":"709","article-title":"Coded distributed computing for inverse problems","author":"yang","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref57","first-page":"1","article-title":"CodeNet: Training large scale neural networks in presence of soft-errors","author":"dutta","year":"2019","journal-title":"Proc Workshop Coding Theory Large-Scale Mach Learn Int Conf Mach Learn (ICML)"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2017.8262778"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2018.8636047"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2017.2674671"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2012.6284026"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2019.2917855"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/2408776.2408794"},{"key":"ref11","author":"kumar","year":"1994","journal-title":"Introduction to Parallel Computing Design and Analysis of Algorithms"},{"key":"ref40","first-page":"4302","article-title":"Gradient coding from cyclic MDS codes and expander graphs","author":"raviv","year":"2018","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/0167-8191(87)90060-3"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/BF02165411"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2556647.2556660"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-20943-2"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/MSST.2010.5496972"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TC.1984.1676475"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511803253"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2015.7447112"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/2637364.2592042"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2847220.2847223"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2627369.2627664"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2014.140518"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MSPEC.2016.7420396"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/VLSIT.2016.7573377"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2016.7852335"},{"key":"ref9","first-page":"1","article-title":"High-performance hardware for machine learning","author":"william","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3199524.3199564"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3152042.3152047"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ISTC.2016.7593105"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2017.8006960"},{"key":"ref42","first-page":"5606","article-title":"Communication-computation efficient gradient coding","author":"ye","year":"2018","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref41","article-title":"Improving distributed gradient descent using Reed–Solomon codes","author":"halbawi","year":"2017","journal-title":"arXiv 1706 05436"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2019.2904055"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2017.8262881"}],"container-title":["IEEE Transactions on Information Theory"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielaam\/18\/8836351\/8758338-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/18\/8836351\/08758338.pdf?arnumber=8758338","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T21:07:58Z","timestamp":1657746478000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8758338\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10]]},"references-count":66,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tit.2019.2927558","relation":{},"ISSN":["0018-9448","1557-9654"],"issn-type":[{"value":"0018-9448","type":"print"},{"value":"1557-9654","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10]]}}}