{"id":"https://openalex.org/W4405716306","doi":"https://doi.org/10.48550/arxiv.2412.16079","title":"Fair Distributed Machine Learning with Imbalanced Data as a Stackelberg Evolutionary Game","display_name":"Fair Distributed Machine Learning with Imbalanced Data as a Stackelberg Evolutionary Game","publication_year":2024,"publication_date":"2024-12-20","ids":{"openalex":"https://openalex.org/W4405716306","doi":"https://doi.org/10.48550/arxiv.2412.16079"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2412.16079","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.16079","pdf_url":"https://arxiv.org/pdf/2412.16079","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2412.16079","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081352088","display_name":"Sebastian Niehaus","orcid":"https://orcid.org/0000-0003-1291-6836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niehaus, Sebastian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078023563","display_name":"Ingo Roeder","orcid":"https://orcid.org/0000-0002-6741-0608"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roeder, Ingo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5085986753","display_name":"Nico Scherf","orcid":"https://orcid.org/0000-0003-4003-9121"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Scherf, Nico","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9638000130653381,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9638000130653381,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11182","display_name":"Auction Theory and Applications","score":0.9072999954223633,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/stackelberg-competition","display_name":"Stackelberg competition","score":0.9087789058685303},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6144708395004272},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5105565786361694},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3917703926563263},{"id":"https://openalex.org/keywords/mathematical-economics","display_name":"Mathematical economics","score":0.23903560638427734},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.16569435596466064}],"concepts":[{"id":"https://openalex.org/C199510392","wikidata":"https://www.wikidata.org/wiki/Q1184602","display_name":"Stackelberg competition","level":2,"score":0.9087789058685303},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6144708395004272},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5105565786361694},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3917703926563263},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.23903560638427734},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.16569435596466064}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2412.16079","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.16079","pdf_url":"https://arxiv.org/pdf/2412.16079","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2412.16079","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2412.16079","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2412.16079","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.16079","pdf_url":"https://arxiv.org/pdf/2412.16079","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405716306.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Decentralised":[0],"learning":[1,7,46,85],"enables":[2],"the":[3,24,97,104,111,118,131,146],"training":[4,109],"of":[5,26,99,133,172],"deep":[6],"algorithms":[8,94],"without":[9],"centralising":[10],"data":[11,19,27,32,76],"sets,":[12],"resulting":[13],"in":[14,37,44,62,107,139,158],"benefits":[15],"such":[16],"as":[17,86],"improved":[18],"privacy,":[20],"operational":[21],"efficiency":[22],"and":[23,65,74,117],"fostering":[25],"ownership":[28],"policies.":[29],"However,":[30],"significant":[31],"imbalances":[33,58],"pose":[34],"a":[35,167],"challenge":[36],"this":[38,80],"framework.":[39],"Participants":[40],"with":[41,54,162],"smaller":[42],"datasets":[43,128,164],"distributed":[45,84,140],"environments":[47],"often":[48],"achieve":[49],"poorer":[50],"results":[51,143],"than":[52],"participants":[53],"larger":[55,163],"datasets.":[56],"Data":[57],"are":[59,66],"particularly":[60],"pronounced":[61],"medical":[63,127],"fields":[64],"caused":[67],"by":[68,152,156],"different":[69],"patient":[70],"populations,":[71],"technological":[72],"inequalities":[73],"divergent":[75],"collection":[77],"practices.":[78],"In":[79],"paper,":[81],"we":[82],"consider":[83],"an":[87],"Stackelberg":[88,113,120],"evolutionary":[89],"game.":[90],"We":[91,124],"present":[92],"two":[93],"for":[95],"setting":[96],"weights":[98],"each":[100,108],"node's":[101],"contribution":[102],"to":[103,129],"global":[105],"model":[106],"round:":[110],"Deterministic":[112],"Weighting":[114,121],"Model":[115,122],"(DSWM)":[116],"Adaptive":[119],"(ASWM).":[123],"use":[125],"three":[126],"highlight":[130],"impact":[132],"dynamic":[134],"weighting":[135],"on":[136],"underrepresented":[137,150],"nodes":[138,151,161],"learning.":[141],"Our":[142],"show":[144],"that":[145],"ASWM":[147],"significantly":[148],"favours":[149],"improving":[153],"their":[154],"performance":[155,170],"2.713%":[157],"AUC.":[159],"Meanwhile,":[160],"experience":[165],"only":[166],"modest":[168],"average":[169],"decrease":[171],"0.441%.":[173]},"counts_by_year":[],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2024-12-24T00:00:00"}
