{"id":"https://openalex.org/W4403017775","doi":"https://doi.org/10.1145/3641512.3686382","title":"Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning?","display_name":"Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning?","publication_year":2024,"publication_date":"2024-10-01","ids":{"openalex":"https://openalex.org/W4403017775","doi":"https://doi.org/10.1145/3641512.3686382"},"language":"en","primary_location":{"id":"doi:10.1145/3641512.3686382","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3641512.3686382","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-fifth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing","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/A5085838919","display_name":"Peizhong Ju","orcid":"https://orcid.org/0000-0002-4569-3539"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Peizhong Ju","raw_affiliation_strings":["The Ohio State University, Columbus, Ohio, USA"],"raw_orcid":"https://orcid.org/0000-0002-4569-3539","affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, Ohio, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100888007","display_name":"Haibo Yang","orcid":"https://orcid.org/0000-0002-3245-2728"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haibo Yang","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, New York, USA"],"raw_orcid":"https://orcid.org/0000-0002-3245-2728","affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, New York, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100409661","display_name":"Jia Liu","orcid":"https://orcid.org/0000-0001-8844-3233"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jia Liu","raw_affiliation_strings":["The Ohio State University, Columbus, Ohio, United States of America"],"raw_orcid":"https://orcid.org/0000-0001-8844-3233","affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, Ohio, United States of America","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076858296","display_name":"Yingbin Liang","orcid":"https://orcid.org/0000-0002-8635-2992"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingbin Liang","raw_affiliation_strings":["The Ohio State University, Columbus, Ohio, USA"],"raw_orcid":"https://orcid.org/0000-0002-8635-2992","affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, Ohio, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035752536","display_name":"Ness B. Shroff","orcid":"https://orcid.org/0000-0002-4606-6879"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ness Shroff","raw_affiliation_strings":["The Ohio State University, Columbus, Ohio, United States of America"],"raw_orcid":"https://orcid.org/0000-0002-4606-6879","affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, Ohio, United States of America","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5085838919"],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":0.9934,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.80597375,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"141","last_page":"150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9980000257492065,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9800000190734863,"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/generalization","display_name":"Generalization","score":0.8038149476051331},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7278333902359009},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3689923882484436},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35695457458496094},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.32749271392822266},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08488795161247253}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.8038149476051331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7278333902359009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3689923882484436},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35695457458496094},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32749271392822266},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08488795161247253},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3641512.3686382","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3641512.3686382","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-fifth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1556298747","display_name":null,"funder_award_id":"CAREER CNS-2110259","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3180398241","display_name":null,"funder_award_id":"CNS-2106932","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3455827733","display_name":null,"funder_award_id":"W911NF-21-1-0244","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G4402065810","display_name":null,"funder_award_id":"CNS-2106933","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4774960571","display_name":null,"funder_award_id":"CNS-1901057","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5008084248","display_name":null,"funder_award_id":"W911NF-23-2-0225","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"},{"id":"https://openalex.org/G5269070513","display_name":null,"funder_award_id":"ECCS-2331104","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5793290134","display_name":null,"funder_award_id":"2324052","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6130151171","display_name":null,"funder_award_id":"NSF AI Institute (AI-EDGE) CNS-2112471","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7326891288","display_name":null,"funder_award_id":"CNS-2312836","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7408472212","display_name":null,"funder_award_id":"ECCS-2113860","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7946311847","display_name":null,"funder_award_id":"CNS-1955535","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2541884796","https://openalex.org/W2602856279","https://openalex.org/W2787348029","https://openalex.org/W2788067318","https://openalex.org/W2911867426","https://openalex.org/W2922153390","https://openalex.org/W2949522309","https://openalex.org/W2974935988","https://openalex.org/W3003867771","https://openalex.org/W3006555759","https://openalex.org/W3018252856","https://openalex.org/W3100779497","https://openalex.org/W3107100345","https://openalex.org/W3125944278","https://openalex.org/W3126083338","https://openalex.org/W3162554303","https://openalex.org/W3169042981","https://openalex.org/W3177095755","https://openalex.org/W4213464063","https://openalex.org/W4221151561","https://openalex.org/W4238306122","https://openalex.org/W4283783183","https://openalex.org/W4320459812","https://openalex.org/W4320460176","https://openalex.org/W4322624833","https://openalex.org/W4364383562","https://openalex.org/W4386083022","https://openalex.org/W6753958361","https://openalex.org/W6759238902","https://openalex.org/W6765541894","https://openalex.org/W6799962196"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Federated":[0],"Learning":[1],"(FL)":[2],"has":[3,53],"gained":[4],"significant":[5],"popularity":[6],"due":[7,75],"to":[8,65,76,87,225],"its":[9],"effectiveness":[10],"in":[11,92],"training":[12,221],"machine":[13],"learning":[14,43,113],"models":[15],"across":[16],"diverse":[17],"sites":[18],"without":[19],"requiring":[20],"direct":[21],"data":[22,70,100,139],"sharing.":[23],"While":[24],"various":[25],"algorithms":[26],"along":[27],"with":[28,36,50,193],"their":[29],"optimization":[30],"analyses":[31],"have":[32],"shown":[33],"that":[34],"FL":[35,49,82,110,240],"local":[37,51,78,103,168],"updates":[38,52,79,104,169],"is":[39,141],"a":[40,89,121,130,203],"communication-efficient":[41],"distributed":[42],"framework,":[44],"the":[45,66,77,81,97,106,112,134,138,145,155,161,164,167,189,194,211,218,226],"generalization":[46,107,127,190,228],"performance":[47,108,128,191],"of":[48,60,99,125,154,163,166,196,206,213,220],"received":[54],"comparatively":[55],"less":[56],"attention.":[57],"This":[58,84],"lack":[59],"investigation":[61,200],"can":[62],"be":[63],"attributed":[64],"complex":[67],"interplay":[68],"between":[69],"heterogeneity":[71,101,140],"and":[72,102,147,182,186,217],"infrequent":[73],"communication":[74],"within":[80],"framework.":[83],"motivates":[85],"us":[86],"investigate":[88],"fundamental":[90],"question":[91],"FL:":[93],"Can":[94],"we":[95,119,158],"quantify":[96,160],"impact":[98,162],"on":[105],"for":[109,143,238],"as":[111,133,171,235],"process":[114],"evolves?":[115],"To":[116],"this":[117],"end,":[118],"conduct":[120],"comprehensive":[122,204],"theoretical":[123],"study":[124],"FL's":[126],"using":[129],"linear":[131],"model":[132,156,214],"first":[135],"step,":[136],"where":[137],"considered":[142],"both":[144],"stationary":[146],"online/non-stationary":[148],"cases.":[149],"By":[150],"providing":[151],"closed-form":[152],"expressions":[153],"error,":[157],"rigorously":[159],"number":[165,195,212,219],"(denoted":[170],"K)":[172],"under":[173],"three":[174],"settings":[175],"(K":[176],"=":[177,184],"1,":[178],"K":[179,183],"<":[180],"\u221e,":[181],"\u221e)":[185],"show":[187],"how":[188,207],"evolves":[192],"rounds":[197],"t.":[198],"Our":[199],"also":[201],"provides":[202],"understanding":[205],"different":[208],"configurations":[209],"(including":[210],"parameters":[215],"p":[216],"samples":[222],"n)":[223],"contribute":[224],"overall":[227],"performance,":[229],"thus":[230],"shedding":[231],"new":[232],"insights":[233],"(such":[234],"benign":[236],"overfitting)":[237],"implementing":[239],"over":[241],"networks.":[242]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}