{"id":"https://openalex.org/W4306317741","doi":"https://doi.org/10.1145/3511808.3557378","title":"Learning to Generalize in Heterogeneous Federated Networks","display_name":"Learning to Generalize in Heterogeneous Federated Networks","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317741","doi":"https://doi.org/10.1145/3511808.3557378"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557378","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557378","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","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 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5114734448","display_name":"Cen Chen","orcid":"https://orcid.org/0000-0003-0325-1705"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cen Chen","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051708679","display_name":"Tiandi Ye","orcid":"https://orcid.org/0000-0003-0169-457X"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiandi Ye","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Li Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Wang","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101472135","display_name":"Ming Gao","orcid":"https://orcid.org/0000-0002-5603-2680"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Gao","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1808,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.81308574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"159","last_page":"168"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9672999978065491,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9088000059127808,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8017051219940186},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.6686897277832031},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5554792881011963},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5094330906867981},{"id":"https://openalex.org/keywords/data-sharing","display_name":"Data sharing","score":0.4454447329044342},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4119229018688202},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36214667558670044},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3366532325744629}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8017051219940186},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.6686897277832031},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5554792881011963},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5094330906867981},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.4454447329044342},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4119229018688202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36214667558670044},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3366532325744629},{"id":"https://openalex.org/C204787440","wikidata":"https://www.wikidata.org/wiki/Q188504","display_name":"Alternative medicine","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557378","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557378","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","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 31st ACM International Conference on Information &amp; Knowledge Management","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":15,"referenced_works":["https://openalex.org/W385466589","https://openalex.org/W2057907879","https://openalex.org/W2112796928","https://openalex.org/W2612690371","https://openalex.org/W2887280559","https://openalex.org/W2962897020","https://openalex.org/W2971167006","https://openalex.org/W3012255272","https://openalex.org/W3018464563","https://openalex.org/W3021654819","https://openalex.org/W3035668299","https://openalex.org/W3089578458","https://openalex.org/W3099314130","https://openalex.org/W3141797743","https://openalex.org/W4285762978"],"related_works":["https://openalex.org/W4298221930","https://openalex.org/W2777914285","https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W2031695474","https://openalex.org/W3013363440","https://openalex.org/W4287823391","https://openalex.org/W2024136090"],"abstract_inverted_index":{"With":[0],"the":[1,5,10,14,22,48,64,125,129,146,152],"rapid":[2],"development":[3],"of":[4,7,16,25,148,151],"Internet":[6],"Things":[8],"(IoT),":[9],"need":[11],"to":[12,20,75,91],"expand":[13],"amount":[15],"data":[17,35,39,57],"through":[18],"data-sharing":[19],"improve":[21],"model":[23,59],"performance":[24],"edge":[26],"devices":[27],"has":[28,44],"become":[29],"increasingly":[30],"compelling.":[31],"To":[32,62],"effectively":[33],"protect":[34],"privacy":[36],"while":[37],"leveraging":[38],"across":[40,85,115],"silos,":[41],"federated":[42,52,68,135],"learning":[43,53,136],"emerged.":[45],"However,":[46],"in":[47,67,70,133],"real":[49],"world":[50],"applications,":[51],"inevitably":[54],"faeces":[55],"both":[56],"and":[58,87,111],"heterogeneity":[60,65],"challenges.":[61],"address":[63],"issues":[66],"networks,":[69],"this":[71],"work,":[72],"we":[73,96],"seek":[74],"jointly":[76],"learn":[77],"a":[78,98],"global":[79],"feature":[80],"representation":[81],"that":[82,107,124],"is":[83],"robust":[84,110],"clients":[86],"potentially":[88],"also":[89,140],"generalizable":[90,112],"new":[92],"clients.":[93,116],"More":[94],"specifically,":[95],"propose":[97],"personalized":[99],"<u>Fed</u>erated":[100],"optimization":[101],"framework":[102],"with":[103],"<u>M</u>eta":[104],"<u>C</u>ritic":[105],"(FedMC)":[106],"efficiently":[108],"captures":[109],"domain-invariant":[113],"knowledge":[114],"Extensive":[117],"experiments":[118],"on":[119,145],"four":[120],"public":[121],"datasets":[122],"show":[123],"proposed":[126,153],"FedMC":[127],"outperforms":[128],"competing":[130],"state-of-the-art":[131],"methods":[132],"heterogeneous":[134],"settings.":[137],"We":[138],"have":[139],"performed":[141],"detailed":[142],"ablation":[143],"analysis":[144],"importance":[147],"different":[149],"components":[150],"model.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
