{"id":"https://openalex.org/W4285605900","doi":"https://doi.org/10.24963/ijcai.2022/671","title":"Ancestral Instrument Method for Causal Inference without Complete Knowledge","display_name":"Ancestral Instrument Method for Causal Inference without Complete Knowledge","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4285605900","doi":"https://doi.org/10.24963/ijcai.2022/671"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2022/671","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/671","pdf_url":"https://www.ijcai.org/proceedings/2022/0671.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.ijcai.org/proceedings/2022/0671.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065281913","display_name":"Debo Cheng","orcid":"https://orcid.org/0000-0002-0383-1462"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Debo Cheng","raw_affiliation_strings":["University of South Australia","STEM, University of South Australia, Adelaide, SA, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Australia","institution_ids":["https://openalex.org/I170239107"]},{"raw_affiliation_string":"STEM, University of South Australia, Adelaide, SA, Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012177739","display_name":"Jiuyong Li","orcid":"https://orcid.org/0000-0002-9023-1878"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jiuyong Li","raw_affiliation_strings":["University of South Australia","STEM, University of South Australia, Adelaide, SA, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Australia","institution_ids":["https://openalex.org/I170239107"]},{"raw_affiliation_string":"STEM, University of South Australia, Adelaide, SA, Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100383342","display_name":"Lin Liu","orcid":"https://orcid.org/0000-0003-2843-5738"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Lin Liu","raw_affiliation_strings":["University of South Australia","STEM, University of South Australia, Adelaide, SA, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Australia","institution_ids":["https://openalex.org/I170239107"]},{"raw_affiliation_string":"STEM, University of South Australia, Adelaide, SA, Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046882632","display_name":"Jiji Zhang","orcid":"https://orcid.org/0000-0003-0684-2084"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jiji Zhang","raw_affiliation_strings":["Hong Kong Baptist University","Department of Religion and Philosophy, Hong Kong Baptist University, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University","institution_ids":["https://openalex.org/I141568987"]},{"raw_affiliation_string":"Department of Religion and Philosophy, Hong Kong Baptist University, Hong Kong, China","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035846381","display_name":"Thuc Duy Le","orcid":"https://orcid.org/0000-0002-9732-4313"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Thuc Duy Le","raw_affiliation_strings":["University of South Australia","STEM, University of South Australia, Adelaide, SA, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Australia","institution_ids":["https://openalex.org/I170239107"]},{"raw_affiliation_string":"STEM, University of South Australia, Adelaide, SA, Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029442609","display_name":"Jixue Liu","orcid":"https://orcid.org/0000-0002-0794-0404"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jixue Liu","raw_affiliation_strings":["University of South Australia","STEM, University of South Australia, Adelaide, SA, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Australia","institution_ids":["https://openalex.org/I170239107"]},{"raw_affiliation_string":"STEM, University of South Australia, Adelaide, SA, Australia","institution_ids":["https://openalex.org/I170239107"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5065281913"],"corresponding_institution_ids":["https://openalex.org/I170239107"],"apc_list":null,"apc_paid":null,"fwci":0.6231,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.67002385,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4843","last_page":"4849"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9991000294685364,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9991000294685364,"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/T11719","display_name":"Data Quality and Management","score":0.9283000230789185,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9174000024795532,"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/causal-inference","display_name":"Causal inference","score":0.8135956525802612},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.6476297378540039},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5818364024162292},{"id":"https://openalex.org/keywords/confounding","display_name":"Confounding","score":0.5560551881790161},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5447505712509155},{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.5428701639175415},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5306994318962097},{"id":"https://openalex.org/keywords/observational-study","display_name":"Observational study","score":0.47772476077079773},{"id":"https://openalex.org/keywords/instrumental-variable","display_name":"Instrumental variable","score":0.47659701108932495},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.4522455632686615},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41038772463798523},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40805745124816895},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3848552405834198},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35932663083076477},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.35427945852279663},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3303925096988678},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2875014841556549}],"concepts":[{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.8135956525802612},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.6476297378540039},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5818364024162292},{"id":"https://openalex.org/C77350462","wikidata":"https://www.wikidata.org/wiki/Q1125472","display_name":"Confounding","level":2,"score":0.5560551881790161},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5447505712509155},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.5428701639175415},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5306994318962097},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.47772476077079773},{"id":"https://openalex.org/C162144332","wikidata":"https://www.wikidata.org/wiki/Q1665305","display_name":"Instrumental variable","level":2,"score":0.47659701108932495},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.4522455632686615},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41038772463798523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40805745124816895},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3848552405834198},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35932663083076477},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35427945852279663},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3303925096988678},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2875014841556549},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2022/671","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/671","pdf_url":"https://www.ijcai.org/proceedings/2022/0671.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2022/671","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/671","pdf_url":"https://www.ijcai.org/proceedings/2022/0671.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6899999976158142}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320955","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285605900.pdf","grobid_xml":"https://content.openalex.org/works/W4285605900.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W163266900","https://openalex.org/W1513969590","https://openalex.org/W1542581579","https://openalex.org/W1584686383","https://openalex.org/W1991587639","https://openalex.org/W2099274660","https://openalex.org/W2099925654","https://openalex.org/W2114878153","https://openalex.org/W2134652049","https://openalex.org/W2271508620","https://openalex.org/W2768642709","https://openalex.org/W2782130143","https://openalex.org/W2962727190","https://openalex.org/W2963304627","https://openalex.org/W2963831878","https://openalex.org/W2998669122","https://openalex.org/W3103539622","https://openalex.org/W3121584453","https://openalex.org/W3123051034","https://openalex.org/W3150893739","https://openalex.org/W4221140009","https://openalex.org/W4246607039","https://openalex.org/W4299660532","https://openalex.org/W4300197744","https://openalex.org/W4302423442"],"related_works":["https://openalex.org/W4220807758","https://openalex.org/W1847771980","https://openalex.org/W4323042385","https://openalex.org/W3112532512","https://openalex.org/W3155886038","https://openalex.org/W2028447420","https://openalex.org/W3126180043","https://openalex.org/W3215034539","https://openalex.org/W4313422683","https://openalex.org/W4378718308"],"abstract_inverted_index":{"Unobserved":[0],"confounding":[1],"is":[2,37,52],"the":[3,29,45,63,86,104,142,157,164,175,181,208,211],"main":[4],"obstacle":[5],"to":[6,61,117,159],"causal":[7,20,105,135,189],"effect":[8,21,190],"estimation":[9,22,40,191],"from":[10,123],"observational":[11,198],"data.":[12,124,199],"Instrumental":[13],"variables":[14,75],"(IVs)":[15],"are":[16],"widely":[17],"used":[18],"for":[19,81,88,93,134,167,187],"when":[23,33],"there":[24],"exist":[25],"latent":[26,138],"confounders.":[27],"With":[28],"standard":[30,50,66],"IV":[31,36,51,96,171,196,217],"method,":[32],"a":[34,49,71,78,82,90,94,98,119,148,168,193],"given":[35,169,194],"valid,":[38],"unbiased":[39,188],"can":[41],"be":[42],"obtained,":[43],"but":[44],"validity":[46],"requirement":[47,64],"on":[48,70,180,202],"strict":[53],"and":[54,110,155,197,204],"untestable.":[55],"Conditional":[56],"IVs":[57,67,152],"have":[58],"been":[59],"proposed":[60],"relax":[62],"of":[65,73,107,145,150,163,210],"by":[68,128],"conditioning":[69,79,91,120,165],"set":[72,80,92,121,166],"observed":[74,109],"(known":[76],"as":[77],"conditional":[83,95,151],"IV).":[84],"However,":[85],"criterion":[87],"finding":[89],"needs":[97],"directed":[99],"acyclic":[100],"graph":[101],"(DAG)":[102],"representing":[103],"relationships":[106],"both":[108],"unobserved":[111],"variables.":[112],"This":[113],"makes":[114],"it":[115],"challenging":[116],"discover":[118],"directly":[122],"In":[125],"this":[126],"paper,":[127],"leveraging":[129],"maximal":[130],"ancestral":[131,146,170,195],"graphs":[132],"(MAGs)":[133],"inference":[136],"with":[137,192,215],"variables,":[139],"we":[140,183],"study":[141],"graphical":[143],"properties":[144],"IVs,":[147],"type":[149],"using":[153],"MAGs,":[154],"develop":[156,184],"theory":[158],"support":[160],"data-driven":[161],"discovery":[162],"in":[172,213],"data":[173],"under":[174],"pretreatment":[176],"variable":[177],"assumption.":[178],"Based":[179],"theory,":[182],"an":[185],"algorithm":[186,212],"Extensive":[200],"experiments":[201],"synthetic":[203],"real-world":[205],"datasets":[206],"demonstrate":[207],"performance":[209],"comparison":[214],"existing":[216],"methods.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}