{"id":"https://openalex.org/W3024856659","doi":"https://doi.org/10.1109/isit45174.2021.9517986","title":"SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization","display_name":"SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization","publication_year":2021,"publication_date":"2021-07-12","ids":{"openalex":"https://openalex.org/W3024856659","doi":"https://doi.org/10.1109/isit45174.2021.9517986","mag":"3024856659"},"language":"en","primary_location":{"id":"doi:10.1109/isit45174.2021.9517986","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit45174.2021.9517986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2005.07041","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063703765","display_name":"Navjot Singh","orcid":"https://orcid.org/0000-0003-0360-2915"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Navjot Singh","raw_affiliation_strings":["Electrical and Computer Engineering Department, University of California at Los Angeles, Los Angeles, CA, USA","University of California-Los Angeles"],"raw_orcid":"https://orcid.org/0000-0003-0360-2915","affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, University of California at Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California-Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023777978","display_name":"Deepesh Data","orcid":"https://orcid.org/0000-0003-3544-8414"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deepesh Data","raw_affiliation_strings":["Electrical and Computer Engineering Department, University of California at Los Angeles, Los Angeles, CA, USA","University of California Los Angeles,  USA"],"raw_orcid":"https://orcid.org/0000-0003-3544-8414","affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, University of California at Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California Los Angeles,  USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054187846","display_name":"Jemin George","orcid":"https://orcid.org/0000-0001-8417-5411"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]},{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jemin George","raw_affiliation_strings":["U.S. Army Research Laboratory, Adelphi, MD, USA","University of California-Los Angeles"],"raw_orcid":"https://orcid.org/0000-0001-8417-5411","affiliations":[{"raw_affiliation_string":"U.S. Army Research Laboratory, Adelphi, MD, USA","institution_ids":["https://openalex.org/I166416128"]},{"raw_affiliation_string":"University of California-Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083980887","display_name":"Suhas Diggavi","orcid":"https://orcid.org/0000-0001-7313-9861"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suhas Diggavi","raw_affiliation_strings":["Electrical and Computer Engineering Department, University of California at Los Angeles, Los Angeles, CA, USA","University of California Los Angeles,  USA"],"raw_orcid":"https://orcid.org/0000-0001-7313-9861","affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, University of California at Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California Los Angeles,  USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5063703765"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":1.6798,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.8648488,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"2","issue":"3","first_page":"1212","last_page":"1217"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9970999956130981,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9947999715805054,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/momentum","display_name":"Momentum (technical analysis)","score":0.6608278155326843},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.6549032926559448},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.6305593848228455},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5453453063964844},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.5085994005203247},{"id":"https://openalex.org/keywords/convex-function","display_name":"Convex function","score":0.47496363520622253},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.45779141783714294},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45100274682044983},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41718220710754395},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41166672110557556},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3425721824169159},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.3307614326477051},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24236392974853516},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2116939127445221},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.15384900569915771},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11313682794570923},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10122114419937134}],"concepts":[{"id":"https://openalex.org/C60718061","wikidata":"https://www.wikidata.org/wiki/Q1414747","display_name":"Momentum (technical analysis)","level":2,"score":0.6608278155326843},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.6549032926559448},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.6305593848228455},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5453453063964844},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.5085994005203247},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.47496363520622253},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.45779141783714294},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45100274682044983},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41718220710754395},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41166672110557556},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3425721824169159},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.3307614326477051},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24236392974853516},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2116939127445221},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.15384900569915771},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11313682794570923},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10122114419937134},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/isit45174.2021.9517986","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit45174.2021.9517986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},{"id":"doi:10.1109/jsait.2021.3103920","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsait.2021.3103920","pdf_url":null,"source":{"id":"https://openalex.org/S4210211895","display_name":"IEEE Journal on Selected Areas in Information Theory","issn_l":"2641-8770","issn":["2641-8770"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal on Selected Areas in Information Theory","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2005.07041","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.07041","pdf_url":"https://arxiv.org/pdf/2005.07041","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2005.07041","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2005.07041","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"},{"id":"mag:3024856659","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2005.07041","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.07041","pdf_url":"https://arxiv.org/pdf/2005.07041","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1034401897","display_name":null,"funder_award_id":"W911NF-17-2-0196","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1637379582","display_name":null,"funder_award_id":"W911NF-17-2-0196","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"},{"id":"https://openalex.org/G3661900623","display_name":null,"funder_award_id":"1955632","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4407920026","display_name":null,"funder_award_id":"LFR-18-548554","funder_id":"https://openalex.org/F4320308590","funder_display_name":"University of California"},{"id":"https://openalex.org/G473615983","display_name":null,"funder_award_id":"2007714","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5259331294","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320308590","display_name":"University of California","ror":"https://ror.org/00pjdza24"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3024856659.pdf","grobid_xml":"https://content.openalex.org/works/W3024856659.grobid-xml"},"referenced_works_count":76,"referenced_works":["https://openalex.org/W1415242555","https://openalex.org/W1985235885","https://openalex.org/W2019166202","https://openalex.org/W2057929279","https://openalex.org/W2108598243","https://openalex.org/W2166132612","https://openalex.org/W2167183308","https://openalex.org/W2191781618","https://openalex.org/W2194775991","https://openalex.org/W2405578611","https://openalex.org/W2535838896","https://openalex.org/W2547352193","https://openalex.org/W2606891064","https://openalex.org/W2783291400","https://openalex.org/W2808402975","https://openalex.org/W2888561381","https://openalex.org/W2889676205","https://openalex.org/W2890924858","https://openalex.org/W2900182564","https://openalex.org/W2902410171","https://openalex.org/W2911327153","https://openalex.org/W2911863041","https://openalex.org/W2913804488","https://openalex.org/W2944542720","https://openalex.org/W2944602733","https://openalex.org/W2946815927","https://openalex.org/W2962863496","https://openalex.org/W2963000224","https://openalex.org/W2963179579","https://openalex.org/W2963208657","https://openalex.org/W2963228337","https://openalex.org/W2963617134","https://openalex.org/W2963664311","https://openalex.org/W2963766684","https://openalex.org/W2963773265","https://openalex.org/W2963803379","https://openalex.org/W2964004663","https://openalex.org/W2964137440","https://openalex.org/W2971064744","https://openalex.org/W2971342441","https://openalex.org/W2996118901","https://openalex.org/W2996693845","https://openalex.org/W3015640161","https://openalex.org/W3034741284","https://openalex.org/W3038057116","https://openalex.org/W3101036738","https://openalex.org/W3119652720","https://openalex.org/W6628022308","https://openalex.org/W6713835734","https://openalex.org/W6725543821","https://openalex.org/W6728975057","https://openalex.org/W6738250615","https://openalex.org/W6738460352","https://openalex.org/W6738491991","https://openalex.org/W6745458143","https://openalex.org/W6746200960","https://openalex.org/W6746839373","https://openalex.org/W6748019269","https://openalex.org/W6751961731","https://openalex.org/W6752191696","https://openalex.org/W6754341472","https://openalex.org/W6754416507","https://openalex.org/W6754529011","https://openalex.org/W6756561314","https://openalex.org/W6756976665","https://openalex.org/W6758358981","https://openalex.org/W6758557334","https://openalex.org/W6762421227","https://openalex.org/W6762930437","https://openalex.org/W6763393679","https://openalex.org/W6763549698","https://openalex.org/W6765843025","https://openalex.org/W6768660345","https://openalex.org/W6774804355","https://openalex.org/W6777590253","https://openalex.org/W6788502999"],"related_works":["https://openalex.org/W3191152329","https://openalex.org/W2971064744","https://openalex.org/W2963664311","https://openalex.org/W2890924858","https://openalex.org/W2769644379","https://openalex.org/W2963179579","https://openalex.org/W2964004663","https://openalex.org/W2963766684","https://openalex.org/W2963228337","https://openalex.org/W2547352193","https://openalex.org/W3034578623","https://openalex.org/W3175155662","https://openalex.org/W3119652720","https://openalex.org/W3106387899","https://openalex.org/W2886404071","https://openalex.org/W2990061623","https://openalex.org/W2982648258","https://openalex.org/W2982408624","https://openalex.org/W2529853123","https://openalex.org/W3000203168"],"abstract_inverted_index":{"In":[0,22],"this":[1],"paper,":[2],"we":[3],"propose":[4],"and":[5,37,41,64],"analyze":[6],"SQuARM-SGD,":[7,23],"a":[8,20,27,49],"communication-efficient":[9],"algorithm":[10,60],"for":[11,61,80],"decentralized":[12,82],"training":[13],"of":[14,30,58,72,93,97],"large-scale":[15],"machine":[16],"learning":[17],"models":[18],"over":[19],"network.":[21],"each":[24],"node":[25],"performs":[26],"fixed":[28],"number":[29],"local":[31],"SGD":[32,83],"steps":[33],"using":[34],"Nesterov\u2019s":[35],"momentum":[36,85,105,123],"then":[38],"sends":[39],"sparsified":[40],"quantized":[42],"updates":[43,106],"to":[44,69,111],"its":[45],"neighbors":[46],"regulated":[47],"by":[48],"locally":[50],"computable":[51],"triggering":[52],"criterion.":[53],"We":[54,87,100],"provide":[55],"convergence":[56,91],"guarantees":[57],"our":[59,73],"general":[62],"(non-convex)":[63],"convex":[65],"smooth":[66],"objectives,":[67],"which,":[68],"the":[70,76,90,116],"best":[71],"knowledge,":[74],"is":[75],"first":[77],"theoretical":[78],"analysis":[79],"compressed":[81],"with":[84],"updates.":[86,124],"show":[88,102],"that":[89,96,103],"rate":[92],"SQuARM-SGD":[94,108],"matches":[95],"vanilla":[98],"SGD.":[99],"empirically":[101],"including":[104],"in":[107],"can":[109],"lead":[110],"better":[112],"test":[113],"performance":[114],"than":[115],"current":[117],"state-of-the-art":[118],"which":[119],"does":[120],"not":[121],"consider":[122]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}