{"id":"https://openalex.org/W3175054836","doi":"https://doi.org/10.14778/3461535.3463474","title":"Automated feature engineering for algorithmic fairness","display_name":"Automated feature engineering for algorithmic fairness","publication_year":2021,"publication_date":"2021-05-01","ids":{"openalex":"https://openalex.org/W3175054836","doi":"https://doi.org/10.14778/3461535.3463474","mag":"3175054836"},"language":"en","primary_location":{"id":"doi:10.14778/3461535.3463474","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3461535.3463474","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-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/A5060787804","display_name":"Ricardo Salazar","orcid":"https://orcid.org/0000-0003-2180-6022"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Ricardo Salazar","raw_affiliation_strings":["TU Berlin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Berlin","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028895029","display_name":"Felix Neutatz","orcid":"https://orcid.org/0000-0001-8698-8010"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Felix Neutatz","raw_affiliation_strings":["TU Berlin","Technische Universit\u00e4t Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Berlin","institution_ids":["https://openalex.org/I4577782"]},{"raw_affiliation_string":"Technische Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009128577","display_name":"Ziawasch Abedjan","orcid":"https://orcid.org/0000-0002-2846-1373"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]},{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ziawasch Abedjan","raw_affiliation_strings":["Leibniz Universit\u00e4t Hannover","Technische Universit\u00e4t Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leibniz Universit\u00e4t Hannover","institution_ids":["https://openalex.org/I114112103"]},{"raw_affiliation_string":"Technische Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5060787804"],"corresponding_institution_ids":["https://openalex.org/I4577782"],"apc_list":null,"apc_paid":null,"fwci":0.4437,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.70450144,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"14","issue":"9","first_page":"1694","last_page":"1702"},"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":0.9973999857902527,"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":0.9973999857902527,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9972000122070312,"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":0.994700014591217,"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":0.7127145528793335},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5352528691291809},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.34974050521850586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3275804817676544}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7127145528793335},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5352528691291809},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.34974050521850586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3275804817676544},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14778/3461535.3463474","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3461535.3463474","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},{"id":"mag:3175054836","is_oa":false,"landing_page_url":"https://www.vldb.org/pvldb/vol14/p1694-neutatz.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306421142","display_name":"Very Large Data Bases","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"Very Large Data Bases","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1648303880","https://openalex.org/W1961345416","https://openalex.org/W2014352947","https://openalex.org/W2014915963","https://openalex.org/W2035841117","https://openalex.org/W2054658115","https://openalex.org/W2059216172","https://openalex.org/W2063520155","https://openalex.org/W2085487226","https://openalex.org/W2097246321","https://openalex.org/W2100960835","https://openalex.org/W2103482121","https://openalex.org/W2116984840","https://openalex.org/W2119479037","https://openalex.org/W2126105956","https://openalex.org/W2146521249","https://openalex.org/W2149252982","https://openalex.org/W2182361439","https://openalex.org/W2417863416","https://openalex.org/W2550530154","https://openalex.org/W2584781382","https://openalex.org/W2584805976","https://openalex.org/W2594166818","https://openalex.org/W2750585749","https://openalex.org/W2798682670","https://openalex.org/W2889165464","https://openalex.org/W2912095836","https://openalex.org/W2948130259","https://openalex.org/W2949775086","https://openalex.org/W2950538796","https://openalex.org/W2962762307","https://openalex.org/W2962977061","https://openalex.org/W2963453196","https://openalex.org/W2963718755","https://openalex.org/W2964031043","https://openalex.org/W2964132737","https://openalex.org/W2998216295","https://openalex.org/W3013849604","https://openalex.org/W3034997124","https://openalex.org/W3035088225","https://openalex.org/W3086663505","https://openalex.org/W3139834496","https://openalex.org/W3176424296","https://openalex.org/W6638208828"],"related_works":["https://openalex.org/W2960691795","https://openalex.org/W3186437454","https://openalex.org/W2967736040","https://openalex.org/W1829889916","https://openalex.org/W2283375733","https://openalex.org/W69236537","https://openalex.org/W163337105","https://openalex.org/W2101155094","https://openalex.org/W3132183194","https://openalex.org/W3192254112","https://openalex.org/W2105361678","https://openalex.org/W2558054039","https://openalex.org/W2803413084","https://openalex.org/W3112182098","https://openalex.org/W2011366473","https://openalex.org/W2913324419","https://openalex.org/W3180969125","https://openalex.org/W2131073171","https://openalex.org/W3081519150","https://openalex.org/W1983905162"],"abstract_inverted_index":{"One":[0],"of":[1,5,15,30,60],"the":[2,11,28,46,57,79,100,106],"fundamental":[3],"problems":[4],"machine":[6,18,47,107],"ethics":[7],"is":[8,24],"to":[9,26,87,123,129],"avoid":[10],"perpetuation":[12],"and":[13,40,65,133],"amplification":[14],"discrimination":[16],"through":[17],"learning":[19,48,108],"applications.":[20],"In":[21],"particular,":[22],"it":[23,77,102],"desired":[25],"exclude":[27],"influence":[29],"attributes":[31,44,62],"with":[32,99],"sensitive":[33,89],"information,":[34],"such":[35,61],"as":[36],"gender":[37],"or":[38,151],"race,":[39],"other":[41,145],"causally":[42],"related":[43],"on":[45],"task.":[49],"The":[50],"state-of-the-art":[51],"bias":[52],"reduction":[53],"algorithm":[54],"Capuchin":[55],"breaks":[56],"causality":[58],"chain":[59],"by":[63],"adding":[64],"removing":[66],"tuples.":[67],"However,":[68],"this":[69,93],"horizontal":[70],"approach":[71,84],"can":[72],"be":[73,86],"considered":[74],"invasive":[75],"because":[76],"changes":[78],"data":[80],"distribution.":[81],"A":[82],"vertical":[83],"would":[85,94],"prune":[88],"features":[90,126],"entirely.":[91],"While":[92],"ensure":[95],"fairness":[96],"without":[97],"tampering":[98],"data,":[101],"could":[103],"also":[104],"hurt":[105],"accuracy.":[109],"Therefore,":[110],"we":[111],"propose":[112],"a":[113],"novel":[114],"multi-objective":[115],"feature":[116,121],"selection":[117],"strategy":[118],"that":[119,127],"leverages":[120],"construction":[122],"generate":[124],"more":[125],"lead":[128],"both":[130],"high":[131],"accuracy":[132,143],"fairness.":[134,153],"On":[135],"three":[136],"well-known":[137],"datasets,":[138],"our":[139],"system":[140],"achieves":[141],"higher":[142,152],"than":[144],"fairness-aware":[146],"approaches":[147],"while":[148],"maintaining":[149],"similar":[150]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
