{"id":"https://openalex.org/W7137845959","doi":"https://doi.org/10.1609/aaai.v40i25.39189","title":"Best Arm Identification with Biased Contexts","display_name":"Best Arm Identification with Biased Contexts","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137845959","doi":"https://doi.org/10.1609/aaai.v40i25.39189"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i25.39189","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i25.39189","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39189/43150","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39189/43150","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072361278","display_name":"James Cheshire","orcid":"https://orcid.org/0000-0003-4552-5989"},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"James Cheshire","raw_affiliation_strings":["T\u00e9l\u00e9com Paris"],"affiliations":[{"raw_affiliation_string":"T\u00e9l\u00e9com Paris","institution_ids":["https://openalex.org/I12356871"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129685566","display_name":"Stephan Cl\u00e9men\u00e7on","orcid":null},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Stephan Cl\u00e9men\u00e7on","raw_affiliation_strings":["T\u00e9l\u00e9com Paris"],"affiliations":[{"raw_affiliation_string":"T\u00e9l\u00e9com Paris","institution_ids":["https://openalex.org/I12356871"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5072361278"],"corresponding_institution_ids":["https://openalex.org/I12356871"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0990099,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"25","first_page":"20536","last_page":"20543"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.002400000113993883,"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/T11182","display_name":"Auction Theory and Applications","score":0.000699999975040555,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.6317999958992004},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5860999822616577},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.545799970626831},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5205000042915344},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4616999924182892},{"id":"https://openalex.org/keywords/weight-function","display_name":"Weight function","score":0.4593999981880188},{"id":"https://openalex.org/keywords/debiasing","display_name":"Debiasing","score":0.43459999561309814}],"concepts":[{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.6317999958992004},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5860999822616577},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.555899977684021},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.545799970626831},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5223000049591064},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5205000042915344},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4616999924182892},{"id":"https://openalex.org/C134466208","wikidata":"https://www.wikidata.org/wiki/Q1520657","display_name":"Weight function","level":2,"score":0.4593999981880188},{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.43459999561309814},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40950000286102295},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4074000120162964},{"id":"https://openalex.org/C21596040","wikidata":"https://www.wikidata.org/wiki/Q2896771","display_name":"Unimodality","level":2,"score":0.34940001368522644},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C65660741","wikidata":"https://www.wikidata.org/wiki/Q3952743","display_name":"Score","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27889999747276306},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C79610928","wikidata":"https://www.wikidata.org/wiki/Q1656743","display_name":"Parameter identification problem","level":3,"score":0.26100000739097595}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i25.39189","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i25.39189","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39189/43150","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i25.39189","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i25.39189","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39189/43150","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2011461449","display_name":null,"funder_award_id":"ANR-22-EXES-0013","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G52575968","display_name":null,"funder_award_id":"ANR-22-EXES-0013","funder_id":"https://openalex.org/F4320324478","funder_display_name":"Fondation Math\u00e9matique Jacques Hadamard"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"},{"id":"https://openalex.org/F4320324478","display_name":"Fondation Math\u00e9matique Jacques Hadamard","ror":"https://ror.org/0153me927"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7137845959.pdf","grobid_xml":"https://content.openalex.org/works/W7137845959.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"study":[1],"active":[2,135],"mitigation":[3],"of":[4,18,21,80,83,129,157,164,173,192],"selection":[5,158],"bias":[6,159],"in":[7,68,77,108,147],"statistical":[8],"learning.":[9],"That":[10],"is":[11,72],"sequential":[12,166],"maximization":[13],"over":[14],"a":[15,22,27,32,114,148,174,183,189],"set":[16],"A":[17],"the":[19,39,57,78,84,92,121,125,134,138,144,155,162,165,171,197],"expectation":[20],"reward":[23],"function":[24,52,116,205],"R(a,X)":[25],"w.r.t.":[26],"r.v.":[28],"X":[29],"drawn":[30],"from":[31,38],"target":[33,85],"distribution":[34,43,86],"PT":[35,87],"possibly":[36],"different":[37],"(supposedly":[40],"dominating)":[41],"source":[42],"PS":[44],"under":[45,105],"which":[46,56,194],"rewards":[47,61],"are":[48,221],"observed.":[49],"The":[50],"importance":[51],"dPT/dPS":[53],"(x)":[54],"with":[55],"sequentially":[58],"observed":[59],"biased":[60],"should":[62],"be":[63,75,103,216],"ideally":[64],"weighted":[65,131],"being":[66],"unknown":[67],"practice,":[69],"auxiliary":[70],"information":[71],"assumed":[73],"to":[74,119,142,215],"available":[76],"form":[79],"known":[81],"moments":[82,122],"for":[88,196],"debiasing":[89],"purposes.":[90],"In":[91,133,182],"batch":[93],"setting,":[94,136,186],"this":[95],"problem":[96,139,168],"has":[97],"already":[98],"been":[99],"studied":[100],"and":[101,169,202,210],"can":[102],"solved":[104],"certain":[106],"conditions":[107],"two":[109],"successive":[110],"steps:":[111],"1)":[112],"identify":[113],"weight":[115,204],"so":[117],"as":[118,178],"approximate":[120],"2)":[123],"maximize":[124],"resulting":[126],"(empirical":[127],"version":[128],"the)":[130],"reward.":[132],"if":[137],"boils":[140],"down":[141],"identifying":[143],"best":[145],"arm":[146,200],"stochastic":[149],"multi":[150],"armed":[151],"bandit":[152],"(MAB)":[153],"model,":[154],"presence":[156],"strongly":[160],"affects":[161],"complexity":[163],"optimization":[167],"requires":[170],"development":[172],"new":[175],"algorithmic":[176],"approach,":[177],"we":[179,187],"show":[180],"here.":[181],"fixed":[184],"confidence":[185],"introduce":[188],"novel":[190],"notion":[191],"complexity,":[193],"accounts":[195],"balance":[198],"between":[199],"evaluation":[201],"(parametric)":[203],"estimation,":[206],"establish":[207],"lower":[208],"bounds":[209],"propose":[211],"an":[212],"algorithm":[213],"proved":[214],"near":[217],"optimal.":[218],"Theoretical":[219],"guarantees":[220],"backed":[222],"up":[223],"by":[224],"numerical":[225],"results.":[226]},"counts_by_year":[],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2026-03-18T00:00:00"}