{"id":"https://openalex.org/W4313057368","doi":"https://doi.org/10.1162/tacl_a_00512","title":"Learning Fair Representations via Rate-Distortion Maximization","display_name":"Learning Fair Representations via Rate-Distortion Maximization","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4313057368","doi":"https://doi.org/10.1162/tacl_a_00512"},"language":"en","primary_location":{"id":"doi:10.1162/tacl_a_00512","is_oa":true,"landing_page_url":"https://doi.org/10.1162/tacl_a_00512","pdf_url":"https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl_a_00512/2054697/tacl_a_00512.pdf","source":{"id":"https://openalex.org/S2729999759","display_name":"Transactions of the Association for Computational Linguistics","issn_l":"2307-387X","issn":["2307-387X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Association for Computational Linguistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl_a_00512/2054697/tacl_a_00512.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017183605","display_name":"Somnath Basu Roy Chowdhury","orcid":null},"institutions":[{"id":"https://openalex.org/I1333535994","display_name":"University of North Carolina Health Care","ror":"https://ror.org/00qz24g20","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1333535994"]},{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Somnath Basu Roy Chowdhury","raw_affiliation_strings":["UNC Chapel Hill, USA somnath@cs.unc.edu"],"affiliations":[{"raw_affiliation_string":"UNC Chapel Hill, USA somnath@cs.unc.edu","institution_ids":["https://openalex.org/I1333535994","https://openalex.org/I114027177"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041254552","display_name":"Snigdha Chaturvedi","orcid":null},"institutions":[{"id":"https://openalex.org/I1333535994","display_name":"University of North Carolina Health Care","ror":"https://ror.org/00qz24g20","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1333535994"]},{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Snigdha Chaturvedi","raw_affiliation_strings":["UNC Chapel Hill, USA snigdha@cs.unc.edu"],"affiliations":[{"raw_affiliation_string":"UNC Chapel Hill, USA snigdha@cs.unc.edu","institution_ids":["https://openalex.org/I1333535994","https://openalex.org/I114027177"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017183605","https://openalex.org/A5041254552"],"corresponding_institution_ids":["https://openalex.org/I114027177","https://openalex.org/I1333535994"],"apc_list":null,"apc_paid":null,"fwci":0.7976,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76688404,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"10","issue":null,"first_page":"1159","last_page":"1174"},"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":0.9944999814033508,"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":0.9944999814033508,"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":0.9848999977111816,"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":0.9847999811172485,"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":0.8443013429641724},{"id":"https://openalex.org/keywords/debiasing","display_name":"Debiasing","score":0.7236162424087524},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.6915119886398315},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.627616286277771},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.6008220911026001},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5372374653816223},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49121612310409546},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4523587226867676},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4421137869358063},{"id":"https://openalex.org/keywords/distortion-function","display_name":"Distortion function","score":0.412986695766449},{"id":"https://openalex.org/keywords/uncorrelated","display_name":"Uncorrelated","score":0.41204142570495605},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1766183078289032},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09638005495071411},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.08832308650016785},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08399933576583862},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.07684576511383057}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8443013429641724},{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.7236162424087524},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.6915119886398315},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.627616286277771},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.6008220911026001},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5372374653816223},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49121612310409546},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4523587226867676},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4421137869358063},{"id":"https://openalex.org/C2780803321","wikidata":"https://www.wikidata.org/wiki/Q5283073","display_name":"Distortion function","level":3,"score":0.412986695766449},{"id":"https://openalex.org/C169345407","wikidata":"https://www.wikidata.org/wiki/Q8216221","display_name":"Uncorrelated","level":2,"score":0.41204142570495605},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1766183078289032},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09638005495071411},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.08832308650016785},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08399933576583862},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.07684576511383057},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"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/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1162/tacl_a_00512","is_oa":true,"landing_page_url":"https://doi.org/10.1162/tacl_a_00512","pdf_url":"https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl_a_00512/2054697/tacl_a_00512.pdf","source":{"id":"https://openalex.org/S2729999759","display_name":"Transactions of the Association for Computational Linguistics","issn_l":"2307-387X","issn":["2307-387X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Association for Computational Linguistics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7657dd6258354bb58ee762fbd38e456e","is_oa":true,"landing_page_url":"https://doaj.org/article/7657dd6258354bb58ee762fbd38e456e","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Transactions of the Association for Computational Linguistics, Vol 10, Pp 1159-1174 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1162/tacl_a_00512","is_oa":true,"landing_page_url":"https://doi.org/10.1162/tacl_a_00512","pdf_url":"https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl_a_00512/2054697/tacl_a_00512.pdf","source":{"id":"https://openalex.org/S2729999759","display_name":"Transactions of the Association for Computational Linguistics","issn_l":"2307-387X","issn":["2307-387X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Association for Computational Linguistics","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4313057368.pdf","grobid_xml":"https://content.openalex.org/works/W4313057368.grobid-xml"},"referenced_works_count":60,"referenced_works":["https://openalex.org/W1516184288","https://openalex.org/W1607035479","https://openalex.org/W1854884267","https://openalex.org/W2025403586","https://openalex.org/W2048087720","https://openalex.org/W2057978375","https://openalex.org/W2101234009","https://openalex.org/W2142625445","https://openalex.org/W2164931791","https://openalex.org/W2170682101","https://openalex.org/W2187089797","https://openalex.org/W2262564268","https://openalex.org/W2346625195","https://openalex.org/W2524643686","https://openalex.org/W2531638282","https://openalex.org/W2559655401","https://openalex.org/W2575864632","https://openalex.org/W2618735189","https://openalex.org/W2740582239","https://openalex.org/W2771976988","https://openalex.org/W2888161220","https://openalex.org/W2889624842","https://openalex.org/W2909212904","https://openalex.org/W2945985835","https://openalex.org/W2963116854","https://openalex.org/W2963626623","https://openalex.org/W2963879260","https://openalex.org/W2964183365","https://openalex.org/W2964235839","https://openalex.org/W2970211217","https://openalex.org/W2990138404","https://openalex.org/W3035241006","https://openalex.org/W3035664806","https://openalex.org/W3039559565","https://openalex.org/W3104235057","https://openalex.org/W3106003309","https://openalex.org/W3159900299","https://openalex.org/W3165462110","https://openalex.org/W3181414820","https://openalex.org/W3201217479","https://openalex.org/W3214152503","https://openalex.org/W4288347478","https://openalex.org/W6600376888","https://openalex.org/W6639419424","https://openalex.org/W6675354045","https://openalex.org/W6676984168","https://openalex.org/W6680970901","https://openalex.org/W6681262047","https://openalex.org/W6684072790","https://openalex.org/W6691812829","https://openalex.org/W6692617188","https://openalex.org/W6721933647","https://openalex.org/W6731720961","https://openalex.org/W6738077463","https://openalex.org/W6755207826","https://openalex.org/W6757817989","https://openalex.org/W6762664187","https://openalex.org/W6764294493","https://openalex.org/W6780226713","https://openalex.org/W6796386619"],"related_works":["https://openalex.org/W4386875279","https://openalex.org/W4362554880","https://openalex.org/W4281684980","https://openalex.org/W2171721708","https://openalex.org/W3214527415","https://openalex.org/W4287887864","https://openalex.org/W1495104519","https://openalex.org/W4390963114","https://openalex.org/W4225584739","https://openalex.org/W2199432031"],"abstract_inverted_index":{"Abstract":[0],"Text":[1],"representations":[2,21,47,67,102],"learned":[3,101],"by":[4,45,112],"machine":[5],"learning":[6],"models":[7,17],"often":[8],"encode":[9],"undesirable":[10],"demographic":[11],"information":[12,44,83,108],"of":[13,48],"the":[14,52,59],"user.":[15],"Predictive":[16],"based":[18],"on":[19,24,97],"these":[20],"can":[22,77],"rely":[23],"such":[25],"information,":[26],"resulting":[27],"in":[28],"biased":[29],"decisions.":[30],"We":[31],"present":[32],"a":[33,71,113],"novel":[34],"debiasing":[35],"technique,":[36],"Fairness-aware":[37],"Rate":[38],"Maximization":[39],"(FaRM),":[40],"that":[41,92],"removes":[42],"protected":[43,54,86,106],"making":[46],"instances":[49],"belonging":[50],"to":[51,65,81],"same":[53],"attribute":[55,107],"class":[56],"uncorrelated,":[57],"using":[58],"rate-distortion":[60],"function.":[61],"FaRM":[62,76,93],"is":[63],"able":[64],"debias":[66],"with":[68],"or":[69],"without":[70],"target":[72],"task":[73],"at":[74],"hand.":[75],"also":[78],"be":[79],"adapted":[80],"remove":[82],"about":[84],"multiple":[85],"attributes":[87],"simultaneously.":[88],"Empirical":[89],"evaluations":[90],"show":[91],"achieves":[94],"state-of-the-art":[95],"performance":[96],"several":[98],"datasets,":[99],"and":[100],"leak":[103],"significantly":[104],"less":[105],"against":[109],"an":[110],"attack":[111],"non-linear":[114],"probing":[115],"network.":[116]},"counts_by_year":[{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}