{"id":"https://openalex.org/W4415367697","doi":"https://doi.org/10.1109/isit63088.2025.11195384","title":"Communication-Efficient Approximate Gradient Coding Using Structured Matrices","display_name":"Communication-Efficient Approximate Gradient Coding Using Structured Matrices","publication_year":2025,"publication_date":"2025-06-22","ids":{"openalex":"https://openalex.org/W4415367697","doi":"https://doi.org/10.1109/isit63088.2025.11195384"},"language":null,"primary_location":{"id":"doi:10.1109/isit63088.2025.11195384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit63088.2025.11195384","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120072415","display_name":"Sifat Munim","orcid":null},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sifat Munim","raw_affiliation_strings":["Iowa State University,Department of Electrical and Computer Engineering,Ames,IA,U.S.A,50011"],"affiliations":[{"raw_affiliation_string":"Iowa State University,Department of Electrical and Computer Engineering,Ames,IA,U.S.A,50011","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055656185","display_name":"Aditya Ramamoorthy","orcid":"https://orcid.org/0000-0003-3448-1271"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aditya Ramamoorthy","raw_affiliation_strings":["Iowa State University,Department of Electrical and Computer Engineering,Ames,IA,U.S.A,50011"],"affiliations":[{"raw_affiliation_string":"Iowa State University,Department of Electrical and Computer Engineering,Ames,IA,U.S.A,50011","institution_ids":["https://openalex.org/I173911158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5120072415"],"corresponding_institution_ids":["https://openalex.org/I173911158"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33682071,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9508000016212463,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9508000016212463,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12923","display_name":"Digital Image Processing Techniques","score":0.9502000212669373,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9381999969482422,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5683000087738037},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.5159000158309937},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4828000068664551},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.44290000200271606},{"id":"https://openalex.org/keywords/algebraic-number","display_name":"Algebraic number","score":0.4422999918460846},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4041999876499176},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.35269999504089355},{"id":"https://openalex.org/keywords/approximation-theory","display_name":"Approximation theory","score":0.3474000096321106}],"concepts":[{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5683000087738037},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.5159000158309937},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.515500009059906},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4984000027179718},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4828000068664551},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.44290000200271606},{"id":"https://openalex.org/C9376300","wikidata":"https://www.wikidata.org/wiki/Q168817","display_name":"Algebraic number","level":2,"score":0.4422999918460846},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4041999876499176},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.385699987411499},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.36320000886917114},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C145242015","wikidata":"https://www.wikidata.org/wiki/Q774123","display_name":"Approximation theory","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32339999079704285},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.3206999897956848},{"id":"https://openalex.org/C113709454","wikidata":"https://www.wikidata.org/wiki/Q602136","display_name":"Coding theory","level":2,"score":0.319599986076355},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30720001459121704},{"id":"https://openalex.org/C202286095","wikidata":"https://www.wikidata.org/wiki/Q579262","display_name":"Error function","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.295199990272522},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C115680565","wikidata":"https://www.wikidata.org/wiki/Q5977448","display_name":"Gradient method","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.26989999413490295},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit63088.2025.11195384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit63088.2025.11195384","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W585133165","https://openalex.org/W2964323106","https://openalex.org/W2977030270","https://openalex.org/W3035832794","https://openalex.org/W3167719345","https://openalex.org/W4205545339","https://openalex.org/W4205872699","https://openalex.org/W4251007617","https://openalex.org/W4285230246"],"related_works":[],"abstract_inverted_index":{"Large":[0],"scale":[1],"distributed":[2,29],"learning":[3,49],"aims":[4],"at":[5],"minimizing":[6],"a":[7,16,22,34,44,146,186],"loss":[8],"function":[9],"<tex":[10,23,78,104,126],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[11,24,79,105,127],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$L$</tex>":[12],"that":[13,46,73,120,166,200],"depends":[14],"on":[15,190,219],"training":[17],"dataset":[18],"with":[19,178],"respect":[20],"to":[21,52,64,97,107,134,214],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$d$</tex>-length":[25],"parameter":[26,35],"vector.":[27],"The":[28],"cluster":[30],"typically":[31],"consists":[32],"of":[33,61,89,100,125,155,194,223],"server":[36],"(PS)":[37],"and":[38,67,173,180],"multiple":[39],"workers.":[40,54],"Gradient":[41],"coding":[42,69,93,159],"is":[43],"technique":[45],"makes":[47],"the":[48,59,65,74,87,95,108,112,122,138,191,220],"process":[50],"resilient":[51],"straggling":[53],"It":[55],"introduces":[56],"redundancy":[57],"within":[58,130],"assignment":[60],"data":[62],"points":[63],"workers":[66,96],"uses":[68],"theoretic":[70],"ideas":[71],"so":[72],"PS":[75],"can":[76],"recover":[77],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\nabla":[80,128],"L$</tex>":[81,129],"exactly":[82],"or":[83],"approximately,":[84],"even":[85],"in":[86,145,208],"presence":[88],"stragglers.":[90],"Communication-efficient":[91],"gradient":[92,132,158],"allows":[94],"communicate":[98],"vectors":[99],"length":[101],"smaller":[102],"than":[103],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$d$</tex>":[106],"PS,":[109],"thus":[110],"reducing":[111],"communication":[113],"time.":[114],"While":[115],"there":[116],"have":[117,203],"been":[118,143],"schemes":[119,162,202],"address":[121],"exact":[123],"recovery":[124],"communication-efficient":[131,156],"coding,":[133],"our":[135,201,224],"best":[136],"knowledge":[137],"approximate":[139,157],"variant":[140],"has":[141],"not":[142],"considered":[144],"systematic":[147],"manner.":[148],"In":[149],"this":[150],"work,":[151],"we":[152,184,211],"present":[153],"constructions":[154],"schemes.":[160,225],"Our":[161],"use":[163],"structured":[164],"matrices":[165],"arise":[167],"from":[168],"bipartite":[169],"graphs,":[170,176],"combinatorial":[171],"designs":[172],"strongly":[174],"regular":[175],"along":[177],"randomization,":[179],"algebraic":[181],"constraints.":[182],"Moreover,":[183],"derive":[185],"corresponding":[187],"lower":[188],"bound":[189],"approximation":[192,205,221],"error":[193,222],"any":[195],"scheme.":[196],"Numerical":[197],"experiments":[198],"demonstrate":[199],"low":[204],"error.":[206],"Furthermore,":[207],"several":[209],"cases,":[210],"are":[212],"able":[213],"provide":[215],"analytical":[216],"upper":[217],"bounds":[218]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-21T00:00:00"}
