{"id":"https://openalex.org/W4403488202","doi":"https://doi.org/10.3233/faia240590","title":"Fair-OBNC: Correcting Label Noise for Fairer Datasets","display_name":"Fair-OBNC: Correcting Label Noise for Fairer Datasets","publication_year":2024,"publication_date":"2024-10-16","ids":{"openalex":"https://openalex.org/W4403488202","doi":"https://doi.org/10.3233/faia240590"},"language":"en","primary_location":{"id":"doi:10.3233/faia240590","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240590","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240590","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240590","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086695956","display_name":"I. Oliveira e Silva","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"In\u00e2s Oliveira e Silva","raw_affiliation_strings":["Feedzai"],"affiliations":[{"raw_affiliation_string":"Feedzai","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037812412","display_name":"S. M. Jesus","orcid":"https://orcid.org/0000-0002-6021-1761"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"S\u00e9rgio Jesus","raw_affiliation_strings":["Feedzai","Universidade do Porto"],"affiliations":[{"raw_affiliation_string":"Feedzai","institution_ids":[]},{"raw_affiliation_string":"Universidade do Porto","institution_ids":["https://openalex.org/I182534213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002436291","display_name":"Hugo Alexandre Ferreira","orcid":"https://orcid.org/0000-0002-4323-3942"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hugo Ferreira","raw_affiliation_strings":["Feedzai"],"affiliations":[{"raw_affiliation_string":"Feedzai","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039038824","display_name":"Pedro Saleiro","orcid":"https://orcid.org/0000-0003-2750-1692"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pedro Saleiro","raw_affiliation_strings":["Feedzai"],"affiliations":[{"raw_affiliation_string":"Feedzai","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028719572","display_name":"In\u00eas Sousa","orcid":"https://orcid.org/0000-0002-8488-256X"},"institutions":[{"id":"https://openalex.org/I4210157425","display_name":"Fraunhofer Portugal Research","ror":"https://ror.org/05eqk2j25","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210157425","https://openalex.org/I4923324"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"In\u00eas Sousa","raw_affiliation_strings":["Fraunhofer Portugal AICOS"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Portugal AICOS","institution_ids":["https://openalex.org/I4210157425"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077752651","display_name":"Pedro Bizarro","orcid":"https://orcid.org/0000-0001-5281-1970"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pedro Bizarro","raw_affiliation_strings":["Feedzai"],"affiliations":[{"raw_affiliation_string":"Feedzai","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058183984","display_name":"Carlos Soares","orcid":"https://orcid.org/0000-0003-4549-8917"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Carlos Soares","raw_affiliation_strings":["Universidade do Porto"],"affiliations":[{"raw_affiliation_string":"Universidade do Porto","institution_ids":["https://openalex.org/I182534213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5086695956"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38923809,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.8303999900817871,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.8303999900817871,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.8059999942779541,"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/T12617","display_name":"Energy, Environment, and Transportation Policies","score":0.7782999873161316,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.48997583985328674},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.474685400724411},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28917133808135986}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.48997583985328674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.474685400724411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28917133808135986},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia240590","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240590","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240590","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia240590","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240590","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240590","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6100000143051147,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4403488202.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Data":[0],"used":[1],"by":[2],"automated":[3],"decision-making":[4],"systems,":[5],"such":[6,32,59,74],"as":[7,33,43,75],"Machine":[8],"Learning":[9],"models,":[10],"often":[11],"reflects":[12],"discriminatory":[13],"behavior":[14],"that":[15,173],"occurred":[16],"in":[17,22,34,89,147,201,212,220],"the":[18,23,67,90,136,144,148,153,174,178,183,196,202,226],"past.":[19],"These":[20],"biases":[21,68],"training":[24,114],"data":[25,61,204,221],"are":[26,40,87],"sometimes":[27],"related":[28],"to":[29,52,71,112,217],"label":[30,83,105,168,186,230],"noise,":[31],"COMPAS,":[35],"where":[36],"more":[37],"African-American":[38],"offenders":[39],"wrongly":[41],"labeled":[42],"having":[44],"a":[45,104],"higher":[46],"risk":[47],"of":[48,131,138,140,152,166,185,191,195,210,229],"recidivism":[49],"when":[50,215],"compared":[51,216],"their":[53],"White":[54],"counterparts.":[55],"Models":[56,199],"trained":[57,200,219],"on":[58,94,135,208],"biased":[60],"may":[62],"perpetuate":[63],"or":[64,78],"even":[65],"aggravate":[66],"with":[69,109,116,127,222],"respect":[70],"sensitive":[72],"information,":[73],"gender,":[76],"race,":[77],"age.":[79],"However,":[80],"while":[81],"multiple":[82],"noise":[84,106],"correction":[85,107,187],"approaches":[86],"available":[88],"literature,":[91],"these":[92],"focus":[93],"model":[95],"performance":[96],"exclusively.":[97],"In":[98],"this":[99],"work,":[100],"we":[101],"propose":[102],"Fair-OBNC,":[103],"method":[108,122,176],"fairness":[110],"considerations,":[111],"produce":[113],"datasets":[115],"measurable":[117],"demographic":[118,150,213],"parity.":[119],"The":[120],"presented":[121],"adapts":[123],"Ordering-Based":[124],"Noise":[125],"Correction,":[126],"an":[128,141,206],"adjusted":[129],"criterion":[130],"ordering,":[132],"based":[133],"both":[134],"margin":[137],"error":[139],"ensemble,":[142],"and":[143],"potential":[145],"increase":[146],"observed":[149],"parity":[151],"dataset.":[154],"We":[155],"evaluate":[156],"Fair-OBNC":[157],"against":[158],"other":[159],"different":[160,164],"pre-processing":[161],"techniques,":[162],"under":[163],"scenarios":[165],"controlled":[167],"noise.":[169,231],"Our":[170],"results":[171],"show":[172],"proposed":[175],"is":[177],"overall":[179],"better":[180,193],"alternative":[181],"within":[182],"pool":[184],"methods,":[188],"being":[189],"capable":[190],"attaining":[192],"reconstructions":[194],"original":[197],"labels.":[198],"corrected":[203],"have":[205],"increase,":[207],"average,":[209],"150%":[211],"parity,":[214],"models":[218],"noisy":[223],"labels,":[224],"across":[225],"considered":[227],"levels":[228]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
