{"id":"https://openalex.org/W3197007109","doi":"https://doi.org/10.1109/isit45174.2021.9517723","title":"The Impact of Split Classifiers on Group Fairness","display_name":"The Impact of Split Classifiers on Group Fairness","publication_year":2021,"publication_date":"2021-07-12","ids":{"openalex":"https://openalex.org/W3197007109","doi":"https://doi.org/10.1109/isit45174.2021.9517723","mag":"3197007109"},"language":"en","primary_location":{"id":"doi:10.1109/isit45174.2021.9517723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit45174.2021.9517723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-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/A5101897731","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0002-4800-5471"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hao Wang","raw_affiliation_strings":["Harvard University"],"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086525718","display_name":"Hsiang Hsu","orcid":"https://orcid.org/0000-0001-8084-3929"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hsiang Hsu","raw_affiliation_strings":["Harvard University"],"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064392614","display_name":"Mario D\u00edaz","orcid":"https://orcid.org/0000-0002-9321-9815"},"institutions":[{"id":"https://openalex.org/I8961855","display_name":"Universidad Nacional Aut\u00f3noma de M\u00e9xico","ror":"https://ror.org/01tmp8f25","country_code":"MX","type":"education","lineage":["https://openalex.org/I8961855"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Mario Diaz","raw_affiliation_strings":["Universidad Nacional Aut&#x00F3;noma de M&#x00E9;xico","Universidad Nacional Aut\u00f3noma de M\u00e9xico"],"affiliations":[{"raw_affiliation_string":"Universidad Nacional Aut&#x00F3;noma de M&#x00E9;xico","institution_ids":[]},{"raw_affiliation_string":"Universidad Nacional Aut\u00f3noma de M\u00e9xico","institution_ids":["https://openalex.org/I8961855"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074697940","display_name":"Fl\u00e1vio P. Calmon","orcid":"https://orcid.org/0000-0002-7493-1428"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Flavio P. Calmon","raw_affiliation_strings":["Harvard University"],"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101897731"],"corresponding_institution_ids":["https://openalex.org/I2801851002"],"apc_list":null,"apc_paid":null,"fwci":0.2366,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59488821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"3179","last_page":"3184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9061999917030334,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7010964751243591},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.6593571901321411},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6187770366668701},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5766253471374512},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5745024681091309},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.5376718044281006},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.5122470259666443},{"id":"https://openalex.org/keywords/disparate-impact","display_name":"Disparate impact","score":0.4249131977558136},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34776443243026733},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2886744439601898}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7010964751243591},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.6593571901321411},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6187770366668701},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5766253471374512},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5745024681091309},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.5376718044281006},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.5122470259666443},{"id":"https://openalex.org/C2776889015","wikidata":"https://www.wikidata.org/wiki/Q5282532","display_name":"Disparate impact","level":3,"score":0.4249131977558136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34776443243026733},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2886744439601898},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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},{"id":"https://openalex.org/C2778272461","wikidata":"https://www.wikidata.org/wiki/Q190752","display_name":"Supreme court","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit45174.2021.9517723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit45174.2021.9517723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality","score":0.4300000071525574}],"awards":[{"id":"https://openalex.org/G5502197930","display_name":null,"funder_award_id":"1900750,CAREER 1845852,IIS 1926925","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W360270745","https://openalex.org/W1505731132","https://openalex.org/W1511694993","https://openalex.org/W1617650991","https://openalex.org/W1819662813","https://openalex.org/W1966693455","https://openalex.org/W1972568734","https://openalex.org/W2014352947","https://openalex.org/W2016384870","https://openalex.org/W2028770837","https://openalex.org/W2104094955","https://openalex.org/W2147595228","https://openalex.org/W2156557681","https://openalex.org/W2518306676","https://openalex.org/W2524301210","https://openalex.org/W2530395818","https://openalex.org/W2578992305","https://openalex.org/W2732560823","https://openalex.org/W2790025105","https://openalex.org/W2885659818","https://openalex.org/W2912457762","https://openalex.org/W2914427130","https://openalex.org/W2920058944","https://openalex.org/W2946016480","https://openalex.org/W2949200088","https://openalex.org/W2951934011","https://openalex.org/W2963178340","https://openalex.org/W2963286678","https://openalex.org/W2963351127","https://openalex.org/W2963473808","https://openalex.org/W2963608890","https://openalex.org/W2964029263","https://openalex.org/W2964031043","https://openalex.org/W2964675004","https://openalex.org/W2971092532","https://openalex.org/W2988989211","https://openalex.org/W2989000624","https://openalex.org/W2994007361","https://openalex.org/W3006317386","https://openalex.org/W3023309920","https://openalex.org/W3031684522","https://openalex.org/W3101023256","https://openalex.org/W3123374861","https://openalex.org/W3127518054","https://openalex.org/W3200120464","https://openalex.org/W4248633940","https://openalex.org/W4254031250","https://openalex.org/W4288319633","https://openalex.org/W4294568923","https://openalex.org/W4301435544","https://openalex.org/W4386564360","https://openalex.org/W6636267554","https://openalex.org/W6675588070","https://openalex.org/W6727155660","https://openalex.org/W6728551298","https://openalex.org/W6740797850","https://openalex.org/W6748039686","https://openalex.org/W6758760113","https://openalex.org/W6759422604","https://openalex.org/W6760091804","https://openalex.org/W6763285393","https://openalex.org/W6763290930","https://openalex.org/W6764294493","https://openalex.org/W6765646913","https://openalex.org/W6770555144","https://openalex.org/W6771316439","https://openalex.org/W6774071446"],"related_works":["https://openalex.org/W1964832275","https://openalex.org/W2389865566","https://openalex.org/W2407804800","https://openalex.org/W2197698372","https://openalex.org/W2388864896","https://openalex.org/W2888937984","https://openalex.org/W2031173026","https://openalex.org/W2031651184","https://openalex.org/W2117265009","https://openalex.org/W2913388591"],"abstract_inverted_index":{"Disparate":[0],"treatment":[1],"occurs":[2],"when":[3,90],"a":[4,17,37,75,151,158],"machine":[5],"learning":[6],"model":[7,38],"produces":[8],"different":[9,114],"decisions":[10],"for":[11,82,123,143],"groups":[12],"of":[13,47,54,169],"individuals":[14],"based":[15],"on":[16,63],"sensitive":[18,76],"attribute":[19],"(e.g.,":[20],"age,":[21],"sex).":[22],"In":[23],"domains":[24],"where":[25,150],"prediction":[26],"accuracy":[27],"is":[28,95,172],"paramount,":[29],"it":[30],"could":[31],"potentially":[32],"be":[33,128],"acceptable":[34],"to":[35],"fit":[36],"which":[39,71,126,146],"exhibits":[40],"disparate":[41,48],"treatment.":[42],"To":[43],"evaluate":[44],"the":[45,52,80,84,91,98,124,144,163],"effect":[46],"treatment,":[49],"we":[50,117],"compare":[51],"performance":[53,85,115,160],"split":[55,164],"classifiers":[56,58,68,70,89],"(i.e.,":[57,69],"trained":[59],"and":[60,140],"deployed":[61],"separately":[62],"each":[64],"group)":[65],"with":[66],"group-blind":[67,152],"do":[72],"not":[73],"use":[74],"attribute).":[77],"We":[78],"introduce":[79],"benefit-of-splitting":[81,99,125,145],"quantifying":[83],"improvement":[86],"by":[87,131],"splitting":[88],"underlying":[92],"data":[93],"distribution":[94],"known.":[96],"Computing":[97],"directly":[100],"from":[101,157,162],"its":[102],"definition":[103],"involves":[104],"solving":[105,132],"optimization":[106],"problems":[107],"over":[108],"an":[109,120],"infinite-dimensional":[110],"functional":[111],"space.":[112],"Under":[113],"measures,":[116],"(i)":[118],"prove":[119],"equivalent":[121],"expression":[122],"can":[127],"efficiently":[129],"computed":[130],"small-scale":[133],"convex":[134],"programs;":[135],"(ii)":[136],"provide":[137],"sharp":[138],"upper":[139],"lower":[141],"bounds":[142],"reveal":[147],"precise":[148],"conditions":[149],"classifier":[153],"will":[154],"always":[155],"suffer":[156],"non-trivial":[159],"gap":[161],"classifiers.":[165],"A":[166],"full":[167],"version":[168],"this":[170],"paper":[171],"accessible":[173],"at":[174],"[1].":[175]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-14T06:41:57.775601","created_date":"2025-10-10T00:00:00"}
