{"id":"https://openalex.org/W4400034331","doi":"https://doi.org/10.1109/msn60784.2023.00072","title":"Adaptive and Efficient Participant Selection in Vertical Federated Learning","display_name":"Adaptive and Efficient Participant Selection in Vertical Federated Learning","publication_year":2023,"publication_date":"2023-12-14","ids":{"openalex":"https://openalex.org/W4400034331","doi":"https://doi.org/10.1109/msn60784.2023.00072"},"language":"en","primary_location":{"id":"doi:10.1109/msn60784.2023.00072","doi":"https://doi.org/10.1109/msn60784.2023.00072","is_oa":false,"landing_page_url":"https://doi.org/10.1109/msn60784.2023.00072","pdf_url":null,"source":{"id":"https://openalex.org/S4363608365","display_name":"International Conference on Mobility, Sensing and Networking (MSN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2023 19th International Conference on Mobility, Sensing and Networking (MSN)","raw_type":"proceedings-article"},"volume":null,"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/A5114973731","display_name":"Jiahui Huang","orcid":"https://orcid.org/0009-0004-7444-0436","observed_orcids":["https://orcid.org/0009-0004-7444-0436","https://orcid.org/0009-0009-1181-5583"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahui Huang","raw_affiliation_strings":["University of Science and Technology of China,School of Computer Science and Technology,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,School of Computer Science and Technology,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100322320","display_name":"Lan Zhang","orcid":"https://orcid.org/0000-0003-1004-8588","observed_orcids":["https://orcid.org/0000-0003-1004-8588"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan Zhang","raw_affiliation_strings":["University of Science and Technology of China,School of Computer Science and Technology,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,School of Computer Science and Technology,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000173131","display_name":"Anran Li","orcid":"https://orcid.org/0000-0002-3592-4153","observed_orcids":["https://orcid.org/0000-0002-3592-4153"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anran Li","raw_affiliation_strings":["University of Science and Technology of China,School of Computer Science and Technology,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,School of Computer Science and Technology,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101410252","display_name":"Haoran Cheng","orcid":"https://orcid.org/0000-0002-9844-5168","observed_orcids":["https://orcid.org/0000-0002-9844-5168","https://orcid.org/0009-0007-1693-1597"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Cheng","raw_affiliation_strings":["University of Science and Technology of China,School of Computer Science and Technology,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,School of Computer Science and Technology,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004171626","display_name":"Jiexin Xu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiexin Xu","raw_affiliation_strings":["China Merchants Bank,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Merchants Bank,China","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Hongmei Song","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongmei Song","raw_affiliation_strings":["China Merchants Bank,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Merchants Bank,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5326,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67797672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"455","last_page":"462"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.0,"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/T10237","display_name":"Cryptography and Data Security","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/vertical-federated-learning","display_name":"vertical federated learning","score":1.0},{"id":"https://openalex.org/keywords/subject-choice","display_name":"participant selection","score":0.9580000042915344},{"id":"https://openalex.org/keywords/communication-overhead","display_name":"communication overhead","score":0.6579999923706055},{"id":"https://openalex.org/keywords/positive-selection","display_name":"positive selection","score":0.6480000019073486},{"id":"https://openalex.org/keywords/data-privacy","display_name":"data privacy","score":0.6629999876022339}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7390074729919434},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6867730617523193},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.4705184996128082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3961726725101471}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/msn60784.2023.00072","doi":"https://doi.org/10.1109/msn60784.2023.00072","is_oa":false,"landing_page_url":"https://doi.org/10.1109/msn60784.2023.00072","pdf_url":null,"source":{"id":"https://openalex.org/S4363608365","display_name":"International Conference on Mobility, Sensing and Networking (MSN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2023 19th International Conference on Mobility, Sensing and Networking (MSN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2043772506","https://openalex.org/W2131824593","https://openalex.org/W2134206624","https://openalex.org/W2541884796","https://openalex.org/W2701059868","https://openalex.org/W2750384547","https://openalex.org/W2750765126","https://openalex.org/W2912213068","https://openalex.org/W3004117333","https://openalex.org/W3041966875","https://openalex.org/W3049595782","https://openalex.org/W3095593352","https://openalex.org/W3099106497","https://openalex.org/W3154335119","https://openalex.org/W3162275801","https://openalex.org/W3169198323","https://openalex.org/W3176798257","https://openalex.org/W4206504654","https://openalex.org/W4206507136","https://openalex.org/W4212774754","https://openalex.org/W4283800079","https://openalex.org/W4289533960","https://openalex.org/W4386260658","https://openalex.org/W4386260712"],"related_works":["https://openalex.org/W4416250653","https://openalex.org/W4406376724","https://openalex.org/W4289816670","https://openalex.org/W4413360203","https://openalex.org/W4392158231","https://openalex.org/W7135111286","https://openalex.org/W4293057268","https://openalex.org/W4408048521","https://openalex.org/W7081923928","https://openalex.org/W4407480078"],"abstract_inverted_index":{"Vertical":[0],"Federated":[1],"Learning":[2],"(VFL)":[3],"enables":[4],"multiple":[5],"data":[6,16],"owners":[7],"to":[8,28,66,84,110,121],"collaboratively":[9],"train":[10],"a":[11,81,91,100,130,152],"global":[12],"model,":[13],"while":[14,149],"preserving":[15],"privacy.":[17],"However,":[18],"significant":[19],"communication":[20,69,86,136,147,168],"overhead":[21,148],"arises":[22],"during":[23],"the":[24,29,39,42,73,113,123,160],"training":[25],"phase":[26],"due":[27],"transmission":[30],"of":[31,41,75,115,125,181],"massive":[32],"encrypted":[33],"intermediate":[34],"results.":[35],"Our":[36],"investigation":[37],"into":[38],"performance":[40,61,134],"model":[43,133],"with":[44,177],"varying":[45],"participant":[46,77,103],"numbers":[47],"reveals":[48],"that":[49,127,143],"increasing":[50],"participants,":[51,117],"especially":[52],"in":[53,72,106,155,159],"larger":[54],"groups,":[55],"may":[56],"not":[57],"necessarily":[58],"yield":[59],"substantial":[60],"improvements.":[62],"Instead,":[63],"it":[64,89],"tends":[65],"introduce":[67],"additional":[68],"overhead.":[70,137],"Therefore,":[71],"context":[74],"VFL,":[76,107],"selection":[78,104],"emerges":[79],"as":[80,118,120],"crucial":[82],"strategy":[83],"mitigate":[85],"cost,":[87],"though":[88],"remains":[90],"relatively":[92],"unexplored":[93],"domain.":[94],"In":[95],"this":[96],"work,":[97],"we":[98],"propose":[99],"novel":[101],"adaptive":[102],"method":[105],"named":[108],"VFLMG,":[109],"dynamically":[111],"determine":[112],"number":[114],"selected":[116],"well":[119],"identify":[122],"group":[124],"participants":[126],"best":[128],"strikes":[129],"balance":[131],"between":[132],"and":[135,162,173,184],"Evaluations":[138],"on":[139],"various":[140],"datasets":[141],"show":[142],"VFLMG":[144,166],"significantly":[145],"reduces":[146,167],"only":[150],"causing":[151],"minimal":[153],"loss":[154],"accuracy.":[156],"For":[157],"instance,":[158],"MNIST":[161,164],"Fashion":[163],"datasets,":[165],"costs":[169],"by":[170],"32.1":[171],"%":[172,175,183],"27.6":[174],"respectively,":[176],"an":[178],"accuracy":[179],"drop":[180],"0.5":[182],"0.3":[185],"%.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2024-06-27T00:00:00"}