{"id":"https://openalex.org/W4403488538","doi":"https://doi.org/10.3233/faia240570","title":"Making Fair Classification via Correlation Alignment","display_name":"Making Fair Classification via Correlation Alignment","publication_year":2024,"publication_date":"2024-10-16","ids":{"openalex":"https://openalex.org/W4403488538","doi":"https://doi.org/10.3233/faia240570"},"language":"en","primary_location":{"id":"doi:10.3233/faia240570","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240570","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240570","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/FAIA240570","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052666402","display_name":"Jingran Yang","orcid":"https://orcid.org/0009-0008-6406-9222"},"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":"Jingran Yang","raw_affiliation_strings":["East China Normal University"],"raw_orcid":"https://orcid.org/0009-0008-6406-9222","affiliations":[{"raw_affiliation_string":"East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101749694","display_name":"Lingfeng Zhang","orcid":"https://orcid.org/0000-0002-6427-9587"},"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":"Lingfeng Zhang","raw_affiliation_strings":["East China Normal University"],"raw_orcid":"https://orcid.org/0000-0002-6427-9587","affiliations":[{"raw_affiliation_string":"East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100402899","display_name":"Min Zhang","orcid":"https://orcid.org/0000-0002-3152-4347"},"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":"Min Zhang","raw_affiliation_strings":["East China Normal University"],"raw_orcid":"https://orcid.org/0000-0002-3152-4347","affiliations":[{"raw_affiliation_string":"East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1984,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89690722,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.25220000743865967,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.25220000743865967,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"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/correlation","display_name":"Correlation","score":0.5461477041244507},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41049501299858093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40504008531570435},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3849695026874542},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2900693714618683},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.09927371144294739}],"concepts":[{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5461477041244507},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41049501299858093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40504008531570435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3849695026874542},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2900693714618683},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09927371144294739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia240570","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240570","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240570","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/faia240570","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240570","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240570","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":[{"score":0.5299999713897705,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"},{"score":0.46000000834465027,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4403488538.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/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Machine":[0],"learning":[1,29,48],"learns":[2],"patterns":[3],"from":[4],"data":[5],"to":[6],"improve":[7,139],"the":[8,11,58,61,65,79,84,89,143],"performance":[9],"of":[10,67,83,91,110],"decision-making":[12],"systems":[13],"through":[14],"computing,":[15],"and":[16,35,112,122,128,141],"gradually":[17],"affects":[18],"people\u2019s":[19],"lives.":[20],"However,":[21],"it":[22],"shows":[23],"that":[24,100],"in":[25,46,60,70,118,147],"current":[26],"research":[27],"machine":[28,47],"algorithms":[30],"may":[31],"reinforce":[32],"human":[33],"discrimination,":[34],"exacerbate":[36],"negative":[37],"impacts":[38],"on":[39,94],"unprivileged":[40],"groups.":[41],"To":[42],"mitigate":[43,142],"potential":[44],"unfairness":[45],"classifiers,":[49],"we":[50],"propose":[51],"a":[52,119],"fair":[53,144],"classification":[54,120],"approach":[55,93,102,136],"by":[56,77],"quantifying":[57],"difference":[59],"prediction":[62,85],"distribution":[63],"with":[64],"idea":[66],"correlation":[68],"alignment":[69],"transfer":[71],"learning,":[72],"which":[73],"improves":[74],"fairness":[75,129,140],"efficiently":[76],"minimizing":[78],"second-order":[80],"statistical":[81],"distance":[82],"distribution.":[86],"We":[87],"evaluate":[88],"validity":[90],"our":[92,101,135],"four":[95],"real-world":[96],"datasets.":[97],"It":[98],"demonstrates":[99],"significantly":[103],"mitigates":[104],"bias":[105],"w.r.t":[106],"demographic":[107],"parity,":[108],"equality":[109],"opportunity,":[111],"equalized":[113],"odds":[114],"across":[115],"different":[116],"groups":[117],"setting,":[121],"achieves":[123],"better":[124],"trade-off":[125],"between":[126],"accuracy":[127],"than":[130],"previous":[131],"work.":[132],"In":[133],"addition,":[134],"can":[137],"further":[138],"conflict":[145],"problem":[146],"debiased":[148],"networks.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}