{"id":"https://openalex.org/W2947064482","doi":"https://doi.org/10.1109/tsp.2020.3005291","title":"Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data","display_name":"Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2947064482","doi":"https://doi.org/10.1109/tsp.2020.3005291","mag":"2947064482"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2020.3005291","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2020.3005291","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1905.12648","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091389636","display_name":"Shicong Cen","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shicong Cen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066928490","display_name":"Huishuai Zhang","orcid":"https://orcid.org/0000-0003-2711-7295"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huishuai Zhang","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053809095","display_name":"Yuejie Chi","orcid":"https://orcid.org/0000-0002-6766-5459"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuejie Chi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100344522","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0003-0065-3610"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101884287","display_name":"Tie\u2010Yan Liu","orcid":"https://orcid.org/0000-0002-0476-8020"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tie-Yan Liu","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5091389636"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":2.057,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.89199224,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"68","issue":null,"first_page":"3976","last_page":"3989"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":1.0,"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":1.0,"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":0.9969000220298767,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9958000183105469,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6158906817436218},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5726576447486877},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5697434544563293},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5697406530380249},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.538112223148346},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.5131433606147766},{"id":"https://openalex.org/keywords/convex-function","display_name":"Convex function","score":0.4909417927265167},{"id":"https://openalex.org/keywords/empirical-risk-minimization","display_name":"Empirical risk minimization","score":0.41951048374176025},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41353869438171387},{"id":"https://openalex.org/keywords/variance-reduction","display_name":"Variance reduction","score":0.4113956093788147},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.35067999362945557},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34494322538375854}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6158906817436218},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5726576447486877},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5697434544563293},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5697406530380249},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.538112223148346},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.5131433606147766},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.4909417927265167},{"id":"https://openalex.org/C107321475","wikidata":"https://www.wikidata.org/wiki/Q5374254","display_name":"Empirical risk minimization","level":2,"score":0.41951048374176025},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41353869438171387},{"id":"https://openalex.org/C62644790","wikidata":"https://www.wikidata.org/wiki/Q3454689","display_name":"Variance reduction","level":3,"score":0.4113956093788147},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.35067999362945557},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34494322538375854},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"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":2,"locations":[{"id":"doi:10.1109/tsp.2020.3005291","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2020.3005291","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1905.12648","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.12648","pdf_url":"https://arxiv.org/pdf/1905.12648","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1905.12648","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.12648","pdf_url":"https://arxiv.org/pdf/1905.12648","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":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G1469985387","display_name":null,"funder_award_id":"N00014-19-1-2404","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G1580069250","display_name":null,"funder_award_id":"CCF-1901199","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2590387755","display_name":null,"funder_award_id":"CCF-1806154","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3582032785","display_name":null,"funder_award_id":"CCF-2007911","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G854152385","display_name":null,"funder_award_id":"N00014-18-1-2142","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G8597684915","display_name":null,"funder_award_id":"W911NF-18-1-0303","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":99,"referenced_works":["https://openalex.org/W584312462","https://openalex.org/W1574923065","https://openalex.org/W1603765807","https://openalex.org/W1697545848","https://openalex.org/W1939652453","https://openalex.org/W2047152541","https://openalex.org/W2107438106","https://openalex.org/W2116612304","https://openalex.org/W2138243089","https://openalex.org/W2150102617","https://openalex.org/W2152799677","https://openalex.org/W2164278908","https://openalex.org/W2166706236","https://openalex.org/W2216483973","https://openalex.org/W2263561525","https://openalex.org/W2407022425","https://openalex.org/W2510078447","https://openalex.org/W2529853123","https://openalex.org/W2556660792","https://openalex.org/W2557191228","https://openalex.org/W2571425027","https://openalex.org/W2593002563","https://openalex.org/W2617766261","https://openalex.org/W2617960902","https://openalex.org/W2755278809","https://openalex.org/W2766140019","https://openalex.org/W2769644379","https://openalex.org/W2769669795","https://openalex.org/W2774000609","https://openalex.org/W2789243870","https://openalex.org/W2803974531","https://openalex.org/W2804270312","https://openalex.org/W2806414180","https://openalex.org/W2810882972","https://openalex.org/W2889747079","https://openalex.org/W2898280890","https://openalex.org/W2942057781","https://openalex.org/W2949302905","https://openalex.org/W2951101735","https://openalex.org/W2951781666","https://openalex.org/W2952215077","https://openalex.org/W2952552307","https://openalex.org/W2952594493","https://openalex.org/W2962696654","https://openalex.org/W2962696932","https://openalex.org/W2962741697","https://openalex.org/W2963061698","https://openalex.org/W2963122491","https://openalex.org/W2963156201","https://openalex.org/W2963228337","https://openalex.org/W2963335515","https://openalex.org/W2963372166","https://openalex.org/W2963411541","https://openalex.org/W2963540381","https://openalex.org/W2963607709","https://openalex.org/W2963664311","https://openalex.org/W2963734024","https://openalex.org/W2963766684","https://openalex.org/W2963803379","https://openalex.org/W2963992805","https://openalex.org/W2964004663","https://openalex.org/W2964102336","https://openalex.org/W2970527576","https://openalex.org/W3024655380","https://openalex.org/W3086080324","https://openalex.org/W4288333497","https://openalex.org/W4292363360","https://openalex.org/W4297685247","https://openalex.org/W4320927804","https://openalex.org/W6617009369","https://openalex.org/W6637454738","https://openalex.org/W6640396632","https://openalex.org/W6676105031","https://openalex.org/W6680196509","https://openalex.org/W6680402377","https://openalex.org/W6681875376","https://openalex.org/W6682557032","https://openalex.org/W6684249991","https://openalex.org/W6688698367","https://openalex.org/W6693018915","https://openalex.org/W6725585423","https://openalex.org/W6730236268","https://openalex.org/W6730601996","https://openalex.org/W6734370629","https://openalex.org/W6734509502","https://openalex.org/W6738250615","https://openalex.org/W6738460352","https://openalex.org/W6744321884","https://openalex.org/W6745723224","https://openalex.org/W6745964145","https://openalex.org/W6746200960","https://openalex.org/W6748632073","https://openalex.org/W6751888367","https://openalex.org/W6753122105","https://openalex.org/W6754341472","https://openalex.org/W6754651929","https://openalex.org/W6762396932","https://openalex.org/W6764174587","https://openalex.org/W6767560732"],"related_works":["https://openalex.org/W2155195660","https://openalex.org/W2400034325","https://openalex.org/W4292651679","https://openalex.org/W4299515259","https://openalex.org/W2060518740","https://openalex.org/W4367626110","https://openalex.org/W2499557797","https://openalex.org/W2052343155","https://openalex.org/W2262246290","https://openalex.org/W2293758787"],"abstract_inverted_index":{"Stochastic":[0],"variance":[1,43,59,136],"reduced":[2,44,60,137],"methods":[3,61],"have":[4],"gained":[5],"a":[6,51,98,132,192],"lot":[7],"of":[8,41,101,113,128,131,134,158,165,170],"interest":[9],"recently":[10],"for":[11,147],"empirical":[12],"risk":[13],"minimization":[14],"due":[15],"to":[16,37,70,77,86,106,188,205],"its":[17,89],"appealing":[18],"run":[19],"time":[20],"complexity.":[21],"When":[22],"the":[23,39,63,71,111,114,117,125,156,163,168,179],"data":[24,107,172,180],"size":[25,169],"is":[26,82,92],"large":[27],"and":[28,74,84,119,143,167],"disjointly":[29],"stored":[30],"on":[31],"different":[32],"machines,":[33],"it":[34],"becomes":[35],"imperative":[36],"distribute":[38],"implementation":[40],"such":[42],"methods.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49,175],"consider":[50],"general":[52],"framework":[53,81],"that":[54,177,198],"directly":[55],"distributes":[56],"popular":[57],"stochastic":[58,135],"in":[62],"master/slave":[64],"model,":[65],"by":[66,109],"assigning":[67],"outer":[68],"loops":[69,76],"parameter":[72],"server,":[73],"inner":[75],"worker":[78],"machines.":[79],"This":[80],"natural":[83],"friendly":[85],"implement,":[87],"but":[88],"theoretical":[90],"convergence":[91,103,127,157,190],"not":[93],"well":[94],"understood.":[95],"We":[96,123,195],"obtain":[97],"comprehensive":[99],"understanding":[100],"algorithmic":[102],"with":[104],"respect":[105],"homogeneity":[108],"measuring":[110],"smoothness":[112],"discrepancy":[115],"between":[116],"local":[118,171],"global":[120],"loss":[121,208],"functions.":[122,209],"establish":[124],"linear":[126],"distributed":[129,159],"versions":[130],"family":[133],"algorithms,":[138],"including":[139],"those":[140],"using":[141],"accelerated":[142],"recursive":[144],"gradient":[145],"updates,":[146],"minimizing":[148],"strongly":[149],"convex":[150],"losses.":[151],"Our":[152],"theory":[153],"captures":[154],"how":[155],"algorithms":[160],"behaves":[161],"as":[162],"number":[164],"machines":[166],"vary.":[173],"Furthermore,":[174],"show":[176],"when":[178],"are":[181],"less":[182],"balanced,":[183],"regularization":[184],"can":[185,201],"be":[186,202],"used":[187],"ensure":[189],"at":[191],"slower":[193],"rate.":[194],"also":[196],"demonstrate":[197],"our":[199],"analysis":[200],"further":[203],"extended":[204],"handle":[206],"nonconvex":[207]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
