{"id":"https://openalex.org/W3115608547","doi":"https://doi.org/10.1109/wcsp49889.2020.9299689","title":"Federated Learning Service Market: A Game Theoretic Analysis","display_name":"Federated Learning Service Market: A Game Theoretic Analysis","publication_year":2020,"publication_date":"2020-10-21","ids":{"openalex":"https://openalex.org/W3115608547","doi":"https://doi.org/10.1109/wcsp49889.2020.9299689","mag":"3115608547"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp49889.2020.9299689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp49889.2020.9299689","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Wireless Communications and Signal Processing (WCSP)","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/A5068060586","display_name":"Lixiao Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixiao Dong","raw_affiliation_strings":["Hubei Key Laboratory of Transportation Internet of Things, Wuhan University of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hubei Key Laboratory of Transportation Internet of Things, Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100354608","display_name":"Yang Zhang","orcid":"https://orcid.org/0000-0001-9229-7689"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Zhang","raw_affiliation_strings":["Hubei Key Laboratory of Transportation Internet of Things, Wuhan University of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hubei Key Laboratory of Transportation Internet of Things, Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2187,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.84648828,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"227","last_page":"232"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.9922000169754028,"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":0.761364758014679},{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.7232115268707275},{"id":"https://openalex.org/keywords/stackelberg-competition","display_name":"Stackelberg competition","score":0.682157039642334},{"id":"https://openalex.org/keywords/service","display_name":"Service (business)","score":0.5088089108467102},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4902206063270569},{"id":"https://openalex.org/keywords/service-provider","display_name":"Service provider","score":0.4691290557384491},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.43231287598609924},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.431227445602417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3920735716819763},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3773813545703888},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.27353477478027344},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.20480746030807495},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.11564618349075317},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.09349343180656433}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.761364758014679},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.7232115268707275},{"id":"https://openalex.org/C199510392","wikidata":"https://www.wikidata.org/wiki/Q1184602","display_name":"Stackelberg competition","level":2,"score":0.682157039642334},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.5088089108467102},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4902206063270569},{"id":"https://openalex.org/C116537","wikidata":"https://www.wikidata.org/wiki/Q2169973","display_name":"Service provider","level":3,"score":0.4691290557384491},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.43231287598609924},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.431227445602417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3920735716819763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3773813545703888},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.27353477478027344},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.20480746030807495},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.11564618349075317},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.09349343180656433},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcsp49889.2020.9299689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp49889.2020.9299689","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.5400000214576721,"display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1598833883","https://openalex.org/W1965908392","https://openalex.org/W2072671275","https://openalex.org/W2078204127","https://openalex.org/W2103276803","https://openalex.org/W2154725692","https://openalex.org/W2581979418","https://openalex.org/W2769445799","https://openalex.org/W2784249485","https://openalex.org/W2795719186","https://openalex.org/W2972882814","https://openalex.org/W2978422189","https://openalex.org/W2981066294","https://openalex.org/W3003720212","https://openalex.org/W3015636663","https://openalex.org/W6635826773"],"related_works":["https://openalex.org/W1983811306","https://openalex.org/W2365093105","https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W2358742051","https://openalex.org/W2516405122","https://openalex.org/W2900704290","https://openalex.org/W4224009465","https://openalex.org/W3035214865","https://openalex.org/W3115608547"],"abstract_inverted_index":{"Federated":[0],"learning":[1,35,38,47,80,84,91,97,105],"enables":[2],"data":[3,15,21,24,61,68,93,111,115,129,136,173],"owners":[4,62,94,112],"in":[5,149,171],"intelligent":[6],"communication":[7],"systems":[8],"to":[9,33,60,82,98,122,133],"share":[10],"information":[11,100,109],"without":[12],"revealing":[13],"actual":[14],"contents.":[16],"In":[17,72,89],"federated":[18,79,96],"learning,":[19],"each":[20],"owner":[22],"trains":[23,45],"locally,":[25],"and":[26,43,70,113,140,174],"only":[27],"uploads":[28],"the":[29,52,77,90,119,142,147,150,168,172],"corresponding":[30],"trained":[31,55],"gradient":[32],"a":[34,46,83,104,152,158],"server.":[36],"The":[37,54],"server":[39],"aggregates":[40],"collected":[41],"gradients":[42],"further":[44],"model":[48,56,121,175],"by":[49],"averaging":[50],"all":[51,146,167],"gradients.":[53],"can":[57],"be":[58],"returned":[59],"for":[63,135],"improving":[64],"their":[65],"performance":[66],"of":[67,145],"utilization":[69],"analysis.":[71],"this":[73],"work,":[74],"we":[75],"extend":[76],"two-layered":[78],"architecture":[81,154],"market":[85,169],"with":[86,157],"privacy":[87],"preserving.":[88],"market,":[92],"apply":[95],"trade":[99],"extracted":[101],"from":[102,110],"data,":[103],"service":[106,124],"provider":[107],"collects":[108],"provides":[114],"services":[116],"based":[117],"on":[118],"learned":[120],"arbitrary":[123],"users,":[125],"who":[126],"have":[127],"no":[128],"but":[130],"are":[131],"willing":[132],"pay":[134],"services.":[137],"To":[138],"analyze":[139],"solve":[141],"optimal":[143],"behaviours":[144],"participants":[148,170],"system,":[151],"market-oriented":[153],"is":[155],"formulated":[156],"Stackelberg":[159],"game":[160],"theoretic":[161],"approach,":[162],"considering":[163],"social":[164],"impacts":[165],"among":[166],"trading":[176],"processes.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
