{"id":"https://openalex.org/W3171671666","doi":"https://doi.org/10.1145/3447548.3467395","title":"Uplift Modeling with Generalization Guarantees","display_name":"Uplift Modeling with Generalization Guarantees","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3171671666","doi":"https://doi.org/10.1145/3447548.3467395","mag":"3171671666"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467395","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467395","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},"type":"preprint","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/A5014665715","display_name":"Artem Betlei","orcid":"https://orcid.org/0009-0006-2628-9617"},"institutions":[{"id":"https://openalex.org/I4210104430","display_name":"Laboratoire d'Informatique de Grenoble","ror":"https://ror.org/01c8rcg82","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210104430","https://openalex.org/I4210159245","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210161401","display_name":"Criteo (France)","ror":"https://ror.org/04vyg0r47","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210161401"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Artem Betlei","raw_affiliation_strings":["Criteo AI Lab, Grenoble, France","Laboratoire d'Informatique de Grenoble","Criteo AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab, Grenoble, France","institution_ids":["https://openalex.org/I4210161401"]},{"raw_affiliation_string":"Laboratoire d'Informatique de Grenoble","institution_ids":["https://openalex.org/I4210104430"]},{"raw_affiliation_string":"Criteo AI Lab","institution_ids":["https://openalex.org/I4210161401"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079421133","display_name":"Eustache Diemert","orcid":"https://orcid.org/0000-0003-2240-501X"},"institutions":[{"id":"https://openalex.org/I4210161401","display_name":"Criteo (France)","ror":"https://ror.org/04vyg0r47","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210161401"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Eustache Diemert","raw_affiliation_strings":["Criteo AI Lab, Grenoble, France","Criteo AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab, Grenoble, France","institution_ids":["https://openalex.org/I4210161401"]},{"raw_affiliation_string":"Criteo AI Lab","institution_ids":["https://openalex.org/I4210161401"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044686680","display_name":"Massih-Reza Amini","orcid":"https://orcid.org/0000-0001-9032-4233"},"institutions":[{"id":"https://openalex.org/I4210116758","display_name":"Knowledge Foundation","ror":"https://ror.org/02cbq7e25","country_code":"SE","type":"nonprofit","lineage":["https://openalex.org/I4210116758"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR","SE"],"is_corresponding":false,"raw_author_name":"Massih-Reza Amini","raw_affiliation_strings":["University of Grenoble Alps, Grenoble, France","Algorithms, Principles and TheorIes for collaborative Knowledge acquisition And Learning"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Grenoble Alps, Grenoble, France","institution_ids":["https://openalex.org/I899635006"]},{"raw_affiliation_string":"Algorithms, Principles and TheorIes for collaborative Knowledge acquisition And Learning","institution_ids":["https://openalex.org/I4210116758"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.983,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.94166898,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"55","last_page":"65"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9776999950408936,"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/generalization","display_name":"Generalization","score":0.7704875469207764},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7228259444236755},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6388843059539795},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6368093490600586},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6229475140571594},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6104933619499207},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5732722878456116},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5347033739089966},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4943373203277588},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.48619645833969116},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.476310133934021},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.46104639768600464},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4598340392112732},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4475044012069702},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33127203583717346},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18621698021888733}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7704875469207764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7228259444236755},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6388843059539795},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6368093490600586},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6229475140571594},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6104933619499207},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5732722878456116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5347033739089966},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4943373203277588},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.48619645833969116},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.476310133934021},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.46104639768600464},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4598340392112732},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4475044012069702},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33127203583717346},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18621698021888733},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447548.3467395","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467395","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","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":44,"referenced_works":["https://openalex.org/W1944672","https://openalex.org/W52150908","https://openalex.org/W204142812","https://openalex.org/W393502056","https://openalex.org/W1552767446","https://openalex.org/W1570649553","https://openalex.org/W1603952207","https://openalex.org/W1837490984","https://openalex.org/W1976459656","https://openalex.org/W2011485768","https://openalex.org/W2057521255","https://openalex.org/W2058248640","https://openalex.org/W2063368770","https://openalex.org/W2078658856","https://openalex.org/W2101723727","https://openalex.org/W2111233787","https://openalex.org/W2112065930","https://openalex.org/W2115584760","https://openalex.org/W2120100126","https://openalex.org/W2140899775","https://openalex.org/W2141732327","https://openalex.org/W2148771208","https://openalex.org/W2389937032","https://openalex.org/W2475334473","https://openalex.org/W2475392251","https://openalex.org/W2540093921","https://openalex.org/W2560674852","https://openalex.org/W2602024037","https://openalex.org/W2620393362","https://openalex.org/W2624816748","https://openalex.org/W2785777814","https://openalex.org/W2790955711","https://openalex.org/W2900709881","https://openalex.org/W2949395086","https://openalex.org/W2962695761","https://openalex.org/W2964032386","https://openalex.org/W2996321792","https://openalex.org/W2999961377","https://openalex.org/W3018101991","https://openalex.org/W3097704231","https://openalex.org/W3100743579","https://openalex.org/W4285719527","https://openalex.org/W6676434424","https://openalex.org/W6713134421"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W3160516639","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W4390446658","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2922169395","https://openalex.org/W2387658907"],"abstract_inverted_index":{"In":[0,63,99],"this":[1,128,179],"paper,":[2],"we":[3,130,149],"consider":[4],"the":[5,12,34,67,80,83,92,100,103,114,117,176,189,192],"task":[6],"of":[7,15,42,69,116,178,191,201],"ranking":[8,88],"individuals":[9,73],"based":[10],"on":[11,122,142,155,204],"potential":[13,75],"benefit":[14,76],"being":[16],"\"treated\"":[17],"(e.g.":[18],"by":[19,74,79],"a":[20,40,87,134,147,152,162,198],"drug":[21],"or":[22,26,60],"exposure":[23],"to":[24,29,71,91,120,132,197],"recommendations":[25],"ads),":[27],"referred":[28],"as":[30,55],"Uplift":[31,84],"Modeling":[32],"in":[33,44,51],"literature.":[35],"This":[36],"application":[37],"has":[38],"gained":[39],"surge":[41],"interest":[43],"recent":[45],"years":[46],"and":[47,157,170,187],"it":[48,161],"is":[49,77,110,124],"found":[50],"many":[52],"applications":[53],"such":[54,146],"personalized":[56],"medicine,":[57],"recommender":[58],"systems":[59],"targeted":[61],"advertising.":[62],"real":[64],"life":[65],"scenarios":[66],"capacity":[68,115],"models":[70],"rank":[72],"measured":[78],"Area":[81,95],"Under":[82,96],"Curve":[85],"(AUUC),":[86],"metric":[89],"related":[90],"well":[93],"known":[94],"ROC":[97],"Curve.":[98],"case":[101],"where":[102],"objective":[104,164,195],"function,":[105],"for":[106,184],"learning":[107,163,194],"model":[108,135,148],"parameters,":[109],"different":[111],"from":[112,160],"AUUC,":[113],"resulting":[118],"system":[119],"generalize":[121],"AUUC":[123,156],"limited.":[125],"To":[126,144],"tackle":[127],"issue,":[129],"propose":[131],"learn":[133],"that":[136],"directly":[137],"optimizes":[138],"an":[139],"upper":[140],"bound":[141,154],"AUUC.":[143],"find":[145],"first":[150],"develop":[151],"generalization":[153,180],"then":[158],"derive":[159],"called":[165],"AUUC-max,":[166],"usable":[167],"with":[168],"linear":[169],"deep":[171],"models.":[172],"We":[173],"empirically":[174],"study":[175],"tightness":[177],"bound,":[181],"its":[182],"effectiveness":[183],"hyperparameters":[185],"tuning":[186],"show":[188],"efficiency":[190],"proposed":[193],"compared":[196],"wide":[199],"range":[200],"competitive":[202],"baselines":[203],"two":[205],"classical":[206],"uplift":[207],"modeling":[208],"benchmarks":[209],"using":[210],"real-world":[211],"datasets.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
