{"id":"https://openalex.org/W4224311344","doi":"https://doi.org/10.1145/3485447.3512153","title":"LocFedMix-SL: Localize, Federate, and Mix for Improved Scalability, Convergence, and Latency in Split Learning","display_name":"LocFedMix-SL: Localize, Federate, and Mix for Improved Scalability, Convergence, and Latency in Split Learning","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4224311344","doi":"https://doi.org/10.1145/3485447.3512153"},"language":"en","primary_location":{"id":"doi:10.1145/3485447.3512153","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512153","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/1721.1/146330","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022522788","display_name":"Seungeun Oh","orcid":"https://orcid.org/0000-0002-3508-4588"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Seungeun Oh","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027907258","display_name":"Jihong Park","orcid":"https://orcid.org/0000-0001-7623-6552"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jihong Park","raw_affiliation_strings":["Deakin University, Australia"],"affiliations":[{"raw_affiliation_string":"Deakin University, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022815450","display_name":"Praneeth Vepakomma","orcid":"https://orcid.org/0000-0003-2296-9296"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Praneeth Vepakomma","raw_affiliation_strings":["Massachusetts Institute of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031117986","display_name":"Sihun Baek","orcid":"https://orcid.org/0009-0007-3681-040X"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sihun Baek","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023495279","display_name":"Ramesh Raskar","orcid":"https://orcid.org/0000-0002-3254-3224"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramesh Raskar","raw_affiliation_strings":["Massachusetts Institute of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061429095","display_name":"Mehdi Bennis","orcid":"https://orcid.org/0000-0003-0261-0171"},"institutions":[{"id":"https://openalex.org/I98381234","display_name":"University of Oulu","ror":"https://ror.org/03yj89h83","country_code":"FI","type":"education","lineage":["https://openalex.org/I98381234"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Mehdi Bennis","raw_affiliation_strings":["University of Oulu, Finland"],"affiliations":[{"raw_affiliation_string":"University of Oulu, Finland","institution_ids":["https://openalex.org/I98381234"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027772072","display_name":"Seong\u2010Lyun Kim","orcid":"https://orcid.org/0000-0002-5228-9913"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seong-Lyun Kim","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5022522788"],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":4.9047,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.96285109,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3347","last_page":"3357"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9976999759674072,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9912999868392944,"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/scalability","display_name":"Scalability","score":0.827715277671814},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.7209029793739319},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6542549133300781},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6440854072570801},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4293457269668579},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3200008273124695},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14814752340316772},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09907662868499756},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.049422621726989746}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.827715277671814},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.7209029793739319},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6542549133300781},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6440854072570801},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4293457269668579},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3200008273124695},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14814752340316772},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09907662868499756},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.049422621726989746},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3485447.3512153","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512153","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"},{"id":"pmh:oai:dspace.mit.edu:1721.1/146330","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/146330","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ACM|Proceedings of the ACM Web Conference 2022","raw_type":"Article"},{"id":"pmh:oai:figshare.com:article/20589978","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/LocFedMix-SL_Localize_Federate_and_Mix_for_Improved_Scalability_Convergence_and_Latency_in_Split_Learning/20589978","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:oulu.fi:nbnfi-fe2023040334843","is_oa":false,"landing_page_url":"http://urn.fi/urn:nbn:fi-fe2023040334843","pdf_url":null,"source":{"id":"https://openalex.org/S4306400284","display_name":"University of Oulu Repository (University of Oulu)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98381234","host_organization_name":"University of Oulu","host_organization_lineage":["https://openalex.org/I98381234"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:dspace.mit.edu:1721.1/146330","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/146330","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ACM|Proceedings of the ACM Web Conference 2022","raw_type":"Article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6072120315","display_name":null,"funder_award_id":"funded","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1607198972","https://openalex.org/W2963209930","https://openalex.org/W2979359324","https://openalex.org/W2992308087","https://openalex.org/W2995191368","https://openalex.org/W2998028735","https://openalex.org/W3036376900","https://openalex.org/W3129336662"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W2965083567","https://openalex.org/W2393741509","https://openalex.org/W1982914007","https://openalex.org/W2159583675","https://openalex.org/W1824242903","https://openalex.org/W1493858311","https://openalex.org/W2155470929","https://openalex.org/W2111125783","https://openalex.org/W2394465510"],"abstract_inverted_index":{"Split":[0],"learning":[1,7],"(SL)":[2],"is":[3,24,39,122],"a":[4,27,31,125,137,196],"promising":[5],"distributed":[6],"framework":[8],"that":[9,38,142,206],"enables":[10],"to":[11,108,123,173,216],"utilize":[12],"the":[13,73,76,117,143,152,160,168,176,222],"huge":[14],"data":[15,65],"and":[16,58,68,133,154,167,190,213,230],"parallel":[17,92,104,127,148,155,198,224],"computing":[18,156],"resources":[19],"of":[20,79,94,119,146],"mobile":[21,43],"devices.":[22],"SL":[23,54,80,95,105,128,149,199,218,225],"built":[25],"upon":[26],"model-split":[28,153],"architecture,":[29],"wherein":[30],"server":[32],"stores":[33],"an":[34],"upper":[35],"model":[36,48,162],"segment":[37],"shared":[40],"by":[41,61,115,183],"different":[42],"clients":[44,67],"storing":[45],"its":[46],"lower":[47],"segments.":[49],"Without":[50],"exchanging":[51],"raw":[52],"data,":[53],"achieves":[55,208],"high":[56,86],"accuracy":[57],"fast":[59,131],"convergence":[60,112,132,211],"only":[62],"uploading":[63],"smashed":[64],"from":[66,72,151,175],"downloading":[69],"global":[70],"gradients":[71],"server.":[74],"Nonetheless,":[75],"original":[77],"implementation":[78,93],"sequentially":[81],"serves":[82],"multiple":[83],"clients,":[84],"incurring":[85],"latency":[87],"with":[88,130],"many":[89],"clients.":[90],"A":[91],"has":[96],"great":[97],"potential":[98],"in":[99],"reducing":[100],"latency,":[101,214],"yet":[102],"existing":[103,147],"algorithms":[106,226],"resort":[107],"compromising":[109],"scalability":[110],"and/or":[111],"speed.":[113],"Motivated":[114],"this,":[116],"goal":[118],"this":[120,181],"article":[121],"develop":[124],"scalable":[126],"algorithm":[129],"low":[134],"latency.":[135],"As":[136],"first":[138],"step,":[139],"we":[140,194],"identify":[141],"fundamental":[144],"bottleneck":[145],"comes":[150],"architectures,":[157],"under":[158],"which":[159],"server-client":[161],"updates":[163],"are":[164,171],"often":[165],"imbalanced,":[166],"client":[169],"models":[170],"prone":[172],"detach":[174],"server\u2019s":[177],"model.":[178],"To":[179],"fix":[180],"problem,":[182],"carefully":[184],"integrating":[185],"local":[186],"parallelism,":[187],"federated":[188],"learning,":[189],"mixup":[191],"augmentation":[192],"techniques,":[193],"propose":[195],"novel":[197],"framework,":[200],"coined":[201],"LocFedMix-SL.":[202],"Simulation":[203],"results":[204],"corroborate":[205],"LocFedMix-SL":[207],"improved":[209],"scalability,":[210],"speed,":[212],"compared":[215],"sequential":[217],"as":[219,221,228],"well":[220],"state-of-the-art":[223],"such":[227],"SplitFed":[229],"LocSplitFed.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}