{"id":"https://openalex.org/W4414359142","doi":"https://doi.org/10.24963/ijcai.2025/1240","title":"Ensuring Reliable and Transparent Algorithmic Fairness Through Optimal Transport and Uncertainty Quantification","display_name":"Ensuring Reliable and Transparent Algorithmic Fairness Through Optimal Transport and Uncertainty Quantification","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414359142","doi":"https://doi.org/10.24963/ijcai.2025/1240"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/1240","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/1240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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/A5113108506","display_name":"Agathe Fernandes Machado","orcid":null},"institutions":[{"id":"https://openalex.org/I159129438","display_name":"Universit\u00e9 du Qu\u00e9bec \u00e0 Montr\u00e9al","ror":"https://ror.org/002rjbv21","country_code":"CA","type":"education","lineage":["https://openalex.org/I159129438","https://openalex.org/I49663120"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Agathe Fernandes Machado","raw_affiliation_strings":["Universit\u00e9 du Qu\u00e9bec \u00e0 Montr\u00e9al"],"affiliations":[{"raw_affiliation_string":"Universit\u00e9 du Qu\u00e9bec \u00e0 Montr\u00e9al","institution_ids":["https://openalex.org/I159129438"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5113108506"],"corresponding_institution_ids":["https://openalex.org/I159129438"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13926181,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"10971","last_page":"10972"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8636999726295471,"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":0.8636999726295471,"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/transparency","display_name":"Transparency (behavior)","score":0.6952999830245972},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.6212999820709229},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.5972999930381775},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.5145000219345093},{"id":"https://openalex.org/keywords/attribution","display_name":"Attribution","score":0.4641000032424927},{"id":"https://openalex.org/keywords/measurement-uncertainty","display_name":"Measurement uncertainty","score":0.44449999928474426}],"concepts":[{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.6952999830245972},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6869000196456909},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.6212999820709229},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.5972999930381775},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.5145000219345093},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.4641000032424927},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.44449999928474426},{"id":"https://openalex.org/C177803969","wikidata":"https://www.wikidata.org/wiki/Q29205","display_name":"Uncertainty analysis","level":2,"score":0.43639999628067017},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.42660000920295715},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3296000063419342},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.3140000104904175},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.30720001459121704},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C11867375","wikidata":"https://www.wikidata.org/wiki/Q5430671","display_name":"Fairness measure","level":4,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/1240","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/1240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Machine":[0],"learning":[1],"(ML)":[2],"models":[3,111],"are":[4],"increasingly":[5],"used":[6],"in":[7,24,88],"high-stakes":[8],"decisions,":[9],"such":[10],"as":[11],"insurance":[12],"pricing":[13],"and":[14,78,101,114],"pretrial":[15],"detention,":[16],"but":[17],"often":[18],"reproduce":[19],"or":[20],"amplify":[21],"biases":[22],"present":[23],"data.":[25],"To":[26],"mitigate":[27],"discrimination,":[28],"optimal":[29],"transport":[30],"(OT)":[31],"offers":[32],"a":[33],"principled":[34],"way":[35],"to":[36,70,105],"transform":[37],"unfair":[38],"model":[39],"predictions":[40],"into":[41,93],"fair":[42],"ones":[43],"while":[44,59,90],"minimizing":[45],"performance":[46],"loss.":[47],"Moreover,":[48],"uncertainty-based":[49],"methods":[50,104],"like":[51],"calibration":[52,100],"help":[53],"assess":[54],"fairness":[55,73,92],"across":[56],"sensitive":[57],"groups,":[58],"uncertainty":[60,102],"attribution":[61,103],"helps":[62],"identify":[63],"sources":[64],"of":[65,97,109],"bias.":[66],"This":[67],"research":[68],"aims":[69],"address":[71],"algorithmic":[72],"challenges":[74],"by":[75,112],"developing":[76],"evaluation":[77],"mitigation":[79],"techniques":[80],"with":[81],"theoretical":[82],"guarantees":[83],"from":[84],"OT,":[85],"easily":[86],"deployable":[87],"practice,":[89],"integrating":[91],"the":[94],"broader":[95],"framework":[96],"trustworthy":[98],"AI\u2014enhancing":[99],"ensure":[106],"ethical":[107],"use":[108],"ML":[110],"transparency":[113],"reliability.":[115]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
