{"id":"https://openalex.org/W3093272433","doi":"https://doi.org/10.1145/3461702.3462559","title":"FaiR-N: Fair and Robust Neural Networks for Structured Data","display_name":"FaiR-N: Fair and Robust Neural Networks for Structured Data","publication_year":2021,"publication_date":"2021-07-21","ids":{"openalex":"https://openalex.org/W3093272433","doi":"https://doi.org/10.1145/3461702.3462559","mag":"3093272433"},"language":"en","primary_location":{"id":"doi:10.1145/3461702.3462559","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3461702.3462559","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2010.06113","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101916117","display_name":"Shubham Sharma","orcid":"https://orcid.org/0000-0003-3685-8706"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shubham Sharma","raw_affiliation_strings":["University of Texas at Austin, Austin, TX, USA","University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045494697","display_name":"Alan H. Gee","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alan H. Gee","raw_affiliation_strings":["University of Texas at Austin, Austin, TX, USA","University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041507960","display_name":"David Paydarfar","orcid":"https://orcid.org/0000-0002-3244-8104"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Paydarfar","raw_affiliation_strings":["University of Texas at Austin, Austin, TX, USA","University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103071668","display_name":"Joydeep Ghosh","orcid":"https://orcid.org/0000-0002-7366-3548"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joydeep Ghosh","raw_affiliation_strings":["University of Texas at Austin, Austin, TX, USA","University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":0.2748,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.60535345,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"946","last_page":"955"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9986000061035156,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9986000061035156,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.996999979019165,"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"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9480999708175659,"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/robustness","display_name":"Robustness (evolution)","score":0.7441461086273193},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7029485702514648},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6924082040786743},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6559278964996338},{"id":"https://openalex.org/keywords/decision-boundary","display_name":"Decision boundary","score":0.5339772701263428},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4985823631286621},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4765342175960541},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4723930060863495},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4264349639415741},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.4164621829986572},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2466019093990326},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2254517674446106},{"id":"https://openalex.org/keywords/mathematical-economics","display_name":"Mathematical economics","score":0.09078609943389893}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7441461086273193},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7029485702514648},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6924082040786743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6559278964996338},{"id":"https://openalex.org/C42023084","wikidata":"https://www.wikidata.org/wiki/Q5249231","display_name":"Decision boundary","level":3,"score":0.5339772701263428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4985823631286621},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4765342175960541},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4723930060863495},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4264349639415741},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.4164621829986572},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2466019093990326},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2254517674446106},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.09078609943389893},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3461702.3462559","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3461702.3462559","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2010.06113","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.06113","pdf_url":"https://arxiv.org/pdf/2010.06113","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":"text"},{"id":"mag:3093272433","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2010.06113","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2010.06113","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2010.06113","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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:2010.06113","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.06113","pdf_url":"https://arxiv.org/pdf/2010.06113","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3093272433.pdf","grobid_xml":"https://content.openalex.org/works/W3093272433.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W152144363","https://openalex.org/W1961345416","https://openalex.org/W2150997454","https://openalex.org/W2162670686","https://openalex.org/W2540757487","https://openalex.org/W2789346393","https://openalex.org/W2790744245","https://openalex.org/W2888078780","https://openalex.org/W2891340972","https://openalex.org/W2895471314","https://openalex.org/W2921668631","https://openalex.org/W2945151003","https://openalex.org/W2950664378","https://openalex.org/W2963100392","https://openalex.org/W2963116854","https://openalex.org/W2963174898","https://openalex.org/W2964013229","https://openalex.org/W2964483002","https://openalex.org/W2969896603","https://openalex.org/W2983358147","https://openalex.org/W2997532515","https://openalex.org/W2997733093","https://openalex.org/W3005040148","https://openalex.org/W3104997604","https://openalex.org/W3120740533","https://openalex.org/W3122175177","https://openalex.org/W3125041301","https://openalex.org/W4289258088"],"related_works":["https://openalex.org/W3184621883","https://openalex.org/W3176008422","https://openalex.org/W3198438967","https://openalex.org/W2895786087","https://openalex.org/W2288220956","https://openalex.org/W3101136263","https://openalex.org/W3176952330","https://openalex.org/W3155315288","https://openalex.org/W3092357075","https://openalex.org/W3122132572","https://openalex.org/W2947692000","https://openalex.org/W3200944305","https://openalex.org/W3094866301","https://openalex.org/W3035422508","https://openalex.org/W3134631405","https://openalex.org/W3010648303","https://openalex.org/W2751465153","https://openalex.org/W3008972592","https://openalex.org/W3207808314","https://openalex.org/W2982134689"],"abstract_inverted_index":{"Fairness":[0],"and":[1,44,108,136,159,166],"robustness":[2,160],"in":[3,18,96,104],"machine":[4],"learning":[5],"are":[6,10,133,201],"crucial":[7],"when":[8,144],"individuals":[9,103],"subject":[11],"to":[12,57,83,117,120,146,203],"automated":[13],"decisions":[14],"made":[15],"by":[16],"models":[17,127,147],"high-stake":[19],"domains.":[20],"To":[21,185],"promote":[22,121],"ethical":[23],"artificial":[24],"intelligence,":[25],"fairness":[26,49,158,178],"metrics":[27],"that":[28,51,76,88,126,169,180,196],"rely":[29,52,181],"on":[30,53,182],"comparing":[31,54],"model":[32],"error":[33,183],"rates":[34],"across":[35,173,199],"subpopulations":[36],"have":[37,60],"been":[38,61],"widely":[39],"investigated":[40],"for":[41,72],"the":[42,55,78,84,89,94,97,111,118,156,186,193],"detection":[43],"mitigation":[45],"of":[46,80,100,114,188],"bias.":[47],"However,":[48],"measures":[50,179],"ability":[56,99],"achieve":[58],"recourse":[59,101,171,197],"relatively":[62],"unexplored.":[63],"In":[64],"this":[65,130,191],"paper,":[66],"we":[67,163],"present":[68],"a":[69,153],"novel":[70],"formulation":[71],"training":[73],"neural":[74,139,206],"networks":[75],"considers":[77],"distance":[79,113],"data":[81,115],"observations":[82],"decision":[85],"boundary":[86,119],"such":[87],"new":[90,131],"objective:":[91],"(1)":[92],"reduces":[93],"disparity":[95,172,198],"average":[98,112],"between":[102,155],"each":[105],"protected":[106,174],"group,":[107],"(2)":[109],"increases":[110],"points":[116],"adversarial":[122],"robustness.":[123],"We":[124,150],"demonstrate":[125],"trained":[128],"with":[129,141],"objective":[132],"more":[134],"fair":[135],"adversarially":[137],"robust":[138],"networks,":[140],"similar":[142],"accuracies,":[143],"compared":[145],"without":[148],"it.":[149],"also":[151,176],"investigate":[152],"trade-off":[154],"recourse-based":[157],"objectives.":[161],"Moreover,":[162],"qualitatively":[164],"motivate":[165],"empirically":[167],"show":[168],"reducing":[170],"groups":[175,200],"improves":[177],"rates.":[184],"best":[187],"our":[189],"knowledge,":[190],"is":[192],"first":[194],"time":[195],"considered":[202],"train":[204],"fairer":[205],"networks.":[207]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-01T08:55:40.977307","created_date":"2025-10-10T00:00:00"}
