{"id":"https://openalex.org/W4221078811","doi":"https://doi.org/10.3390/e24040461","title":"A Maximal Correlation Framework for Fair Machine Learning","display_name":"A Maximal Correlation Framework for Fair Machine Learning","publication_year":2022,"publication_date":"2022-03-26","ids":{"openalex":"https://openalex.org/W4221078811","doi":"https://doi.org/10.3390/e24040461","pmid":"https://pubmed.ncbi.nlm.nih.gov/35455124"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24040461","pdf_url":"https://www.mdpi.com/1099-4300/24/4/461/pdf?version=1648438593","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/24/4/461/pdf?version=1648438593","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102984971","display_name":"Joshua Lee","orcid":"https://orcid.org/0009-0001-9737-5997"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"funder","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joshua Lee","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007990317","display_name":"Yuheng Bu","orcid":"https://orcid.org/0000-0002-3479-4553"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"funder","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuheng Bu","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060534465","display_name":"Prasanna Sattigeri","orcid":"https://orcid.org/0000-0003-4435-0486"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"funder","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prasanna Sattigeri","raw_affiliation_strings":["MIT-IBM Watson AI Lab, IBM Research, Cambridge, MA 02139, USA"],"affiliations":[{"raw_affiliation_string":"MIT-IBM Watson AI Lab, IBM Research, Cambridge, MA 02139, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049734237","display_name":"Rameswar Panda","orcid":"https://orcid.org/0000-0003-4359-2475"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"funder","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rameswar Panda","raw_affiliation_strings":["MIT-IBM Watson AI Lab, IBM Research, Cambridge, MA 02139, USA"],"affiliations":[{"raw_affiliation_string":"MIT-IBM Watson AI Lab, IBM Research, Cambridge, MA 02139, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066172831","display_name":"Gregory W. Wornell","orcid":"https://orcid.org/0000-0001-9166-4758"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"funder","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gregory W. Wornell","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020676344","display_name":"Leonid Karlinsky","orcid":"https://orcid.org/0000-0003-2524-2068"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"funder","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leonid Karlinsky","raw_affiliation_strings":["MIT-IBM Watson AI Lab, IBM Research, Cambridge, MA 02139, USA"],"affiliations":[{"raw_affiliation_string":"MIT-IBM Watson AI Lab, IBM Research, Cambridge, MA 02139, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052325109","display_name":"Rog\u00e9rio Feris","orcid":"https://orcid.org/0000-0001-6399-0679"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"funder","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rogerio Schmidt Feris","raw_affiliation_strings":["MIT-IBM Watson AI Lab, IBM Research, Cambridge, MA 02139, USA"],"affiliations":[{"raw_affiliation_string":"MIT-IBM Watson AI Lab, IBM Research, Cambridge, MA 02139, USA","institution_ids":["https://openalex.org/I1341412227"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007990317"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.467,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.459002,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":69,"max":75},"biblio":{"volume":"24","issue":"4","first_page":"461","last_page":"461"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9978,"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":0.9978,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9792,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9545,"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/popularity","display_name":"Popularity","score":0.7203177},{"id":"https://openalex.org/keywords/independence","display_name":"Independence","score":0.67147374},{"id":"https://openalex.org/keywords/fairness-measure","display_name":"Fairness measure","score":0.4882348}],"concepts":[{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.7203177},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.714594},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.67147374},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5372522},{"id":"https://openalex.org/C11867375","wikidata":"https://www.wikidata.org/wiki/Q5430671","display_name":"Fairness measure","level":4,"score":0.4882348},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44189173},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42350554},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3571893},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35324562},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23483703},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.11503467},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.071834356},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24040461","pdf_url":"https://www.mdpi.com/1099-4300/24/4/461/pdf?version=1648438593","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":false,"landing_page_url":"https://doaj.org/article/1e8f886c00014d67ac4e07dc8195e2e1","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9027582","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35455124","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24040461","pdf_url":"https://www.mdpi.com/1099-4300/24/4/461/pdf?version=1648438593","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"score":0.78,"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16"}],"grants":[{"funder":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation","award_id":"CCF-1717610"}],"datasets":[],"versions":[],"referenced_works_count":19,"referenced_works":["https://openalex.org/W1961345416","https://openalex.org/W1979769549","https://openalex.org/W1995228946","https://openalex.org/W2014352947","https://openalex.org/W2018582985","https://openalex.org/W2030748132","https://openalex.org/W2107327484","https://openalex.org/W2116984840","https://openalex.org/W2789700415","https://openalex.org/W2897154134","https://openalex.org/W2963100392","https://openalex.org/W2963116854","https://openalex.org/W2963290659","https://openalex.org/W2964031043","https://openalex.org/W2996829667","https://openalex.org/W3034607623","https://openalex.org/W3080361879","https://openalex.org/W3098559293","https://openalex.org/W4229706427"],"related_works":["https://openalex.org/W4294565801","https://openalex.org/W308652608","https://openalex.org/W2952704802","https://openalex.org/W2518037665","https://openalex.org/W2477036161","https://openalex.org/W2384861574","https://openalex.org/W2368605798","https://openalex.org/W2368049389","https://openalex.org/W2348524959","https://openalex.org/W2142306706"],"abstract_inverted_index":{"As":[0],"machine":[1],"learning":[2],"algorithms":[3,66,85],"grow":[4],"in":[5],"popularity":[6],"and":[7,13,44,59,70,91,103,107],"diversify":[8],"to":[9,47,53],"many":[10],"industries,":[11],"ethical":[12],"legal":[14],"concerns":[15],"regarding":[16],"their":[17],"fairness":[18,42,61],"have":[19],"become":[20],"increasingly":[21],"relevant.":[22],"We":[23,81],"explore":[24],"the":[25],"problem":[26],"of":[27,50],"algorithmic":[28],"fairness,":[29],"taking":[30],"an":[31],"information-theoretic":[32],"view.":[33],"The":[34],"maximal":[35],"correlation":[36],"framework":[37],"is":[38,45],"introduced":[39],"for":[40,67],"expressing":[41],"constraints":[43],"shown":[46],"be":[48],"capable":[49],"being":[51],"used":[52],"derive":[54],"regularizers":[55],"that":[56,73,83],"enforce":[57],"independence":[58],"separation-based":[60],"criteria,":[62],"which":[63],"admit":[64],"optimization":[65],"both":[68,98],"discrete":[69,99],"continuous":[71,104],"variables":[72],"are":[74],"more":[75],"computationally":[76],"efficient":[77],"than":[78],"existing":[79],"algorithms.":[80],"show":[82],"these":[84],"provide":[86],"smooth":[87],"performance-fairness":[88],"tradeoff":[89],"curves":[90],"perform":[92],"competitively":[93],"with":[94],"state-of-the-art":[95],"methods":[96],"on":[97],"datasets":[100,105],"(COMPAS,":[101],"Adult)":[102],"(Communities":[106],"Crimes).":[108]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4221078811","counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2025-03-17T02:16:50.029876","created_date":"2022-04-03"}