{"id":"https://openalex.org/W3094478430","doi":"https://doi.org/10.1145/3447548.3467343","title":"Individual Treatment Prescription Effect Estimation in a Low Compliance Setting","display_name":"Individual Treatment Prescription Effect Estimation in a Low Compliance Setting","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3094478430","doi":"https://doi.org/10.1145/3447548.3467343","mag":"3094478430"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467343","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467343","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":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.03235","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010973303","display_name":"Thibaud Rahier","orcid":"https://orcid.org/0000-0002-0886-1249"},"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":"Thibaud Rahier","raw_affiliation_strings":["Criteo AI Lab, Grenoble, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab, Grenoble, France","institution_ids":["https://openalex.org/I4210161401"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023095596","display_name":"Am\u00e9lie H\u00e9liou","orcid":null},"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":"Am\u00e9lie H\u00e9liou","raw_affiliation_strings":["Criteo AI Lab, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab, Paris, France","institution_ids":["https://openalex.org/I4210161401"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105938881","display_name":"Matthieu Martin","orcid":null},"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":"Matthieu Martin","raw_affiliation_strings":["Criteo AI Lab, Grenoble, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab, Grenoble, France","institution_ids":["https://openalex.org/I4210161401"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001047121","display_name":"Christophe Renaudin","orcid":null},"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":"Christophe Renaudin","raw_affiliation_strings":["Criteo AI Lab, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab, Paris, France","institution_ids":["https://openalex.org/I4210161401"]}]},{"author_position":"last","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"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab, Grenoble, France","institution_ids":["https://openalex.org/I4210161401"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01871954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1399","last_page":"1409"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10391","display_name":"Healthcare Policy and Management","score":0.9509999752044678,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11620","display_name":"Medication Adherence and Compliance","score":0.933899998664856,"subfield":{"id":"https://openalex.org/subfields/2714","display_name":"Family Practice"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.8233669996261597},{"id":"https://openalex.org/keywords/medical-prescription","display_name":"Medical prescription","score":0.7944812178611755},{"id":"https://openalex.org/keywords/compliance","display_name":"Compliance (psychology)","score":0.7095276713371277},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.6216804385185242},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5809319019317627},{"id":"https://openalex.org/keywords/fading","display_name":"Fading","score":0.5680248141288757},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.5546678900718689},{"id":"https://openalex.org/keywords/competition","display_name":"Competition (biology)","score":0.548109233379364},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5374904274940491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4603985846042633},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.381870836019516},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3484994173049927},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3216497600078583},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23448950052261353},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.21057933568954468},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1775047779083252},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.17394021153450012},{"id":"https://openalex.org/keywords/nursing","display_name":"Nursing","score":0.08323442935943604}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8233669996261597},{"id":"https://openalex.org/C2426938","wikidata":"https://www.wikidata.org/wiki/Q3355478","display_name":"Medical prescription","level":2,"score":0.7944812178611755},{"id":"https://openalex.org/C2781460075","wikidata":"https://www.wikidata.org/wiki/Q1399332","display_name":"Compliance (psychology)","level":2,"score":0.7095276713371277},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6216804385185242},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5809319019317627},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.5680248141288757},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.5546678900718689},{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.548109233379364},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5374904274940491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4603985846042633},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.381870836019516},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3484994173049927},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3216497600078583},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23448950052261353},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.21057933568954468},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1775047779083252},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.17394021153450012},{"id":"https://openalex.org/C159110408","wikidata":"https://www.wikidata.org/wiki/Q121176","display_name":"Nursing","level":1,"score":0.08323442935943604},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","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":5,"locations":[{"id":"doi:10.1145/3447548.3467343","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467343","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"},{"id":"pmh:oai:arXiv.org:2008.03235","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.03235","pdf_url":"https://arxiv.org/pdf/2008.03235","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:hal-03339108v1","is_oa":true,"landing_page_url":"https://hal.science/hal-03339108","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"KDD 2021, Aug 2021, Singapore (virtual), Singapore. pp.1399-1409, &#x27E8;10.1145/3447548.3467343&#x27E9;","raw_type":"Conference papers"},{"id":"doi:10.48550/arxiv.2008.03235","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2008.03235","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"mag:3094478430","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2008.03235","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.03235","pdf_url":"https://arxiv.org/pdf/2008.03235","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W204142812","https://openalex.org/W1516659296","https://openalex.org/W1603952207","https://openalex.org/W2003336670","https://openalex.org/W2011485768","https://openalex.org/W2037766829","https://openalex.org/W2049073146","https://openalex.org/W2064903582","https://openalex.org/W2101234009","https://openalex.org/W2101626831","https://openalex.org/W2107399972","https://openalex.org/W2136133622","https://openalex.org/W2140899775","https://openalex.org/W2170773736","https://openalex.org/W2208550830","https://openalex.org/W2305754340","https://openalex.org/W2564917231","https://openalex.org/W2622003161","https://openalex.org/W2624816748","https://openalex.org/W2742797692","https://openalex.org/W2764336450","https://openalex.org/W2790955711","https://openalex.org/W2801890059","https://openalex.org/W2804691295","https://openalex.org/W2809468631","https://openalex.org/W2900709881","https://openalex.org/W2917555822","https://openalex.org/W2945458902","https://openalex.org/W2949574684","https://openalex.org/W2950298380","https://openalex.org/W2952993422","https://openalex.org/W2962695761","https://openalex.org/W2962727190","https://openalex.org/W2964032386","https://openalex.org/W2986346803","https://openalex.org/W2989664601","https://openalex.org/W3097704231","https://openalex.org/W3121385028","https://openalex.org/W3121556564","https://openalex.org/W3124557117","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W2184388554","https://openalex.org/W2471507972","https://openalex.org/W3164468267","https://openalex.org/W2914474262","https://openalex.org/W3181124366","https://openalex.org/W3173765562","https://openalex.org/W3157619472","https://openalex.org/W2150319295","https://openalex.org/W2756630952","https://openalex.org/W2765503801","https://openalex.org/W3212147385","https://openalex.org/W2913863092","https://openalex.org/W2965487605","https://openalex.org/W2947673610","https://openalex.org/W3106212003","https://openalex.org/W3035095012","https://openalex.org/W2808540701","https://openalex.org/W3091766268","https://openalex.org/W3158761153","https://openalex.org/W3207493955"],"abstract_inverted_index":{"Individual":[0],"Treatment":[1],"Effect":[2],"(ITE)":[3],"estimation":[4,83],"is":[5],"an":[6],"extensively":[7],"researched":[8],"problem,":[9],"with":[10,124],"applications":[11],"in":[12,32,149],"various":[13],"domains.":[14],"We":[15,76],"model":[16],"the":[17,52,54,56,82,85,99,122,140,143],"case":[18],"where":[19],"there":[20],"exists":[21],"heterogeneous":[22],"non-compliance":[23,36],"to":[24,37,74,94],"a":[25,29,78,108,116],"randomly":[26],"assigned":[27],"treatment,":[28],"typical":[30],"situation":[31],"health":[33],"(because":[34,42],"of":[35,43,58,84,90,142],"prescription)":[38],"or":[39,62],"digital":[40],"advertising":[41],"competition":[44],"and":[45,71,104,114,135],"ad":[46],"blockers":[47],"for":[48,81],"instance).":[49],"The":[50],"lower":[51],"compliance,":[53],"more":[55],"effect":[57,65,112],"treatment":[59],"prescription":[60,64],"-":[61,67],"individual":[63],"(IPE)":[66],"signal":[68,96],"fades":[69],"away":[70],"becomes":[72],"harder":[73],"estimate.":[75],"propose":[77,115],"new":[79],"approach":[80],"IPE":[86,123],"that":[87,138],"takes":[88],"advantage":[89],"observed":[91],"compliance":[92,151],"information":[93],"prevent":[95],"fading.":[97],"Using":[98],"Structural":[100],"Causal":[101],"Model":[102],"framework":[103],"do-calculus,":[105],"we":[106,129],"define":[107],"general":[109],"mediated":[110],"causal":[111],"setting":[113],"corresponding":[117],"estimator":[118],"which":[119,145],"consistently":[120,146],"recovers":[121],"asymptotic":[125],"variance":[126],"guarantees.":[127],"Finally,":[128],"conduct":[130],"experiments":[131],"on":[132],"both":[133],"synthetic":[134],"real-world":[136],"datasets":[137],"highlight":[139],"benefit":[141],"approach,":[144],"improves":[147],"state-of-the-art":[148],"low":[150],"settings.":[152]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
