{"id":"https://openalex.org/W2976492859","doi":"https://doi.org/10.1109/isit.2019.8849580","title":"Distributed Stochastic Gradient Descent Using LDGM Codes","display_name":"Distributed Stochastic Gradient Descent Using LDGM Codes","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2976492859","doi":"https://doi.org/10.1109/isit.2019.8849580","mag":"2976492859"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2019.8849580","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2019.8849580","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5004624497","display_name":"Shunsuke Horii","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shunsuke Horii","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022824333","display_name":"Takahiro Yoshida","orcid":"https://orcid.org/0000-0001-8741-5345"},"institutions":[{"id":"https://openalex.org/I4210124684","display_name":"Yokohama College of Commerce","ror":"https://ror.org/02s5d1b23","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210124684"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Yoshida","raw_affiliation_strings":["Yokohama College of Commerce, Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"Yokohama College of Commerce, Kanagawa, Japan","institution_ids":["https://openalex.org/I4210124684"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101049590","display_name":"Manabu Kobayashi","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Manabu Kobayashi","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110471799","display_name":"Toshiyasu Matsushima","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toshiyasu Matsushima","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5004624497"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":2.7469,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.92656878,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1417","last_page":"1421"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11321","display_name":"Error Correcting Code Techniques","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/gradient-descent","display_name":"Gradient descent","score":0.7196251749992371},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.704885721206665},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6663479804992676},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.577531635761261},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5107619762420654},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.49851512908935547},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4876493215560913},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4763498604297638},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36952459812164307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22835421562194824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20269551873207092},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08706521987915039}],"concepts":[{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.7196251749992371},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.704885721206665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6663479804992676},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.577531635761261},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5107619762420654},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.49851512908935547},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4876493215560913},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4763498604297638},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36952459812164307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22835421562194824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20269551873207092},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08706521987915039},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit.2019.8849580","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2019.8849580","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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":27,"referenced_works":["https://openalex.org/W607505555","https://openalex.org/W1536930200","https://openalex.org/W2107438106","https://openalex.org/W2268702383","https://openalex.org/W2741736887","https://openalex.org/W2751733006","https://openalex.org/W2787128677","https://openalex.org/W2803520071","https://openalex.org/W2952215077","https://openalex.org/W2962850796","https://openalex.org/W2963706835","https://openalex.org/W2964160151","https://openalex.org/W2964352239","https://openalex.org/W2976492859","https://openalex.org/W3100515187","https://openalex.org/W4236362309","https://openalex.org/W4301515685","https://openalex.org/W4302423127","https://openalex.org/W6676105031","https://openalex.org/W6680196509","https://openalex.org/W6730190955","https://openalex.org/W6738835244","https://openalex.org/W6741764668","https://openalex.org/W6742061381","https://openalex.org/W6743655711","https://openalex.org/W6748342376","https://openalex.org/W6751482607"],"related_works":["https://openalex.org/W2895097035","https://openalex.org/W4206903459","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W3020853991","https://openalex.org/W4362706668","https://openalex.org/W4231621013","https://openalex.org/W3171021120","https://openalex.org/W3008318776"],"abstract_inverted_index":{"We":[0],"consider":[1],"a":[2,14,18,37,87,127,165],"distributed":[3,56,128],"learning":[4,57,88],"problem":[5],"in":[6,40,55],"which":[7,46],"the":[8,28,73,79,91,95,110,120,139,153,160,170],"computation":[9],"is":[10,47,84,101,104,117],"carried":[11],"out":[12],"on":[13,67],"system":[15],"consisting":[16],"of":[17,30,169],"master":[19,161],"node":[20,162],"and":[21,113,176],"multiple":[22],"worker":[23],"nodes.":[24],"In":[25,122,138],"such":[26],"systems,":[27],"existence":[29],"slow-running":[31],"machines":[32],"called":[33],"stragglers":[34,54],"will":[35],"cause":[36],"significant":[38],"decrease":[39],"performance.":[41],"Recently,":[42],"coding":[43],"theoretic":[44],"framework,":[45],"named":[48],"Gradient":[49,80,97],"Coding":[50],"(GC),":[51],"for":[52,119],"mitigating":[53],"has":[58],"been":[59],"established":[60],"by":[61],"Tandon":[62],"et":[63],"al.":[64],"Most":[65],"studies":[66],"GC":[68,149],"are":[69],"aiming":[70],"at":[71,172],"recovering":[72],"gradient":[74,111,154,171],"information":[75,155],"completely":[76,108],"assuming":[77],"that":[78],"Descent":[81,98],"(GD)":[82],"algorithm":[83,100],"used":[85],"as":[86],"algorithm.":[89],"On":[90],"other":[92],"hand,":[93],"if":[94],"Stochastic":[96],"(SGD)":[99],"used,":[102],"it":[103,142,158,177],"not":[105],"necessary":[106],"to":[107,151,163,179],"recover":[109,152],"information,":[112],"its":[114],"unbiased":[115,167],"estimator":[116,168],"sufficient":[118],"learning.":[121],"this":[123],"paper,":[124],"we":[125],"propose":[126],"SGD":[129],"scheme":[130],"using":[131],"Low":[132],"Density":[133],"Generator":[134],"Matrix":[135],"(LDGM)":[136],"codes.":[137],"proposed":[140],"system,":[141],"may":[143],"take":[144],"longer":[145],"time":[146],"than":[147],"existing":[148],"methods":[150],"completely,":[156],"however,":[157],"enables":[159],"obtain":[164],"high-quality":[166],"low":[173],"computational":[174],"cost":[175],"leads":[178],"overall":[180],"performance":[181],"improvement.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-14T06:41:57.775601","created_date":"2025-10-10T00:00:00"}