{"id":"https://openalex.org/W2102022980","doi":"https://doi.org/10.1145/1553374.1553389","title":"Structure learning of Bayesian networks using constraints","display_name":"Structure learning of Bayesian networks using constraints","publication_year":2009,"publication_date":"2009-06-14","ids":{"openalex":"https://openalex.org/W2102022980","doi":"https://doi.org/10.1145/1553374.1553389","mag":"2102022980"},"language":"en","primary_location":{"id":"doi:10.1145/1553374.1553389","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1553374.1553389","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th Annual International Conference on Machine Learning","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/A5004994425","display_name":"Cassio P. de Campos","orcid":"https://orcid.org/0000-0001-9130-1287"},"institutions":[{"id":"https://openalex.org/I2614128279","display_name":"Dalle Molle Institute for Artificial Intelligence Research","ror":"https://ror.org/013355g38","country_code":"CH","type":"facility","lineage":["https://openalex.org/I15196421","https://openalex.org/I2614128279","https://openalex.org/I57201433"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Cassio P. de Campos","raw_affiliation_strings":["Dalle Molle Institute for Artificial Intelligence (IDSIA), Switzerland","Dalle Molle Institute for Artificial Intelligence (IDSIA), Switzerland#TAB#"],"affiliations":[{"raw_affiliation_string":"Dalle Molle Institute for Artificial Intelligence (IDSIA), Switzerland","institution_ids":["https://openalex.org/I2614128279"]},{"raw_affiliation_string":"Dalle Molle Institute for Artificial Intelligence (IDSIA), Switzerland#TAB#","institution_ids":["https://openalex.org/I2614128279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003932979","display_name":"Zhi Zeng","orcid":"https://orcid.org/0000-0001-5896-0192"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhi Zeng","raw_affiliation_strings":["Rensselaer Polytechnic Institute (RPI), Troy NY","Rensselaer Polytechnic Institute (RPI) (Troy, NY)"],"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute (RPI), Troy NY","institution_ids":["https://openalex.org/I165799507"]},{"raw_affiliation_string":"Rensselaer Polytechnic Institute (RPI) (Troy, NY)","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076346273","display_name":"Qiang Ji","orcid":"https://orcid.org/0000-0002-4302-2889"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiang Ji","raw_affiliation_strings":["Rensselaer Polytechnic Institute (RPI), Troy NY","Rensselaer Polytechnic Institute (RPI) (Troy, NY)"],"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute (RPI), Troy NY","institution_ids":["https://openalex.org/I165799507"]},{"raw_affiliation_string":"Rensselaer Polytechnic Institute (RPI) (Troy, NY)","institution_ids":["https://openalex.org/I165799507"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004994425"],"corresponding_institution_ids":["https://openalex.org/I2614128279"],"apc_list":null,"apc_paid":null,"fwci":14.4521,"has_fulltext":false,"cited_by_count":121,"citation_normalized_percentile":{"value":0.98986687,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"113","last_page":"120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9998999834060669,"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":0.9998999834060669,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9483000040054321,"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":0.9477999806404114,"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/bayesian-network","display_name":"Bayesian network","score":0.7497380375862122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6744222640991211},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5527462363243103},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.47729337215423584},{"id":"https://openalex.org/keywords/current","display_name":"Current (fluid)","score":0.4473678767681122},{"id":"https://openalex.org/keywords/hill-climbing","display_name":"Hill climbing","score":0.4302453100681305},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.42650750279426575},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4226919710636139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4166056513786316},{"id":"https://openalex.org/keywords/dynamic-programming","display_name":"Dynamic programming","score":0.4114459156990051},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40427476167678833},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.390378475189209},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2286212146282196}],"concepts":[{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.7497380375862122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6744222640991211},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5527462363243103},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.47729337215423584},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.4473678767681122},{"id":"https://openalex.org/C135450995","wikidata":"https://www.wikidata.org/wiki/Q820272","display_name":"Hill climbing","level":2,"score":0.4302453100681305},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.42650750279426575},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4226919710636139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4166056513786316},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.4114459156990051},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40427476167678833},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.390378475189209},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2286212146282196},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1553374.1553389","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1553374.1553389","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th Annual International Conference on Machine Learning","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.149.5070","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.5070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.mcgill.ca/~icml2009/papers/246.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.331.6633","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.331.6633","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ecse.rpi.edu/~qji/Papers/sl.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3684259387","display_name":null,"funder_award_id":"W911NF-06-1-0331","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G5687441399","display_name":null,"funder_award_id":"2009CB320801","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic of China"},{"id":"https://openalex.org/G8197346602","display_name":null,"funder_award_id":"60875044","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321540","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W143237373","https://openalex.org/W1530398305","https://openalex.org/W1551931549","https://openalex.org/W1668219064","https://openalex.org/W1668796269","https://openalex.org/W1789238264","https://openalex.org/W1973734200","https://openalex.org/W1989486129","https://openalex.org/W2008906462","https://openalex.org/W2099900459","https://openalex.org/W2142857211","https://openalex.org/W2165190832","https://openalex.org/W2169152096","https://openalex.org/W2170112109","https://openalex.org/W2223868250","https://openalex.org/W2962899638","https://openalex.org/W2963139738","https://openalex.org/W2997456480","https://openalex.org/W3120740533","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2343247866","https://openalex.org/W4237368524","https://openalex.org/W1232705","https://openalex.org/W2347288419","https://openalex.org/W2476121495","https://openalex.org/W2091546382","https://openalex.org/W2460653416","https://openalex.org/W90886653","https://openalex.org/W2053571861","https://openalex.org/W2186944257"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"exact":[3],"learning":[4],"of":[5,34,107,116],"Bayesian":[6],"network":[7],"structure":[8],"from":[9,98],"data":[10,62,121],"and":[11,31,43,50,58,90,110,113],"expert's":[12],"knowledge":[13],"based":[14],"on":[15],"score":[16,74],"functions":[17],"that":[18,26,55,128],"are":[19],"decomposable.":[20],"First,":[21],"it":[22,84,96],"describes":[23],"useful":[24],"properties":[25,109],"strongly":[27],"reduce":[28],"the":[29,73,86,99,105,108,111,114,117],"time":[30],"memory":[32],"costs":[33],"many":[35],"known":[36],"methods":[37,135],"such":[38],"as":[39],"hill-climbing,":[40],"dynamic":[41],"programming":[42],"sampling":[44],"variable":[45],"orderings.":[46],"Secondly,":[47],"a":[48,64],"branch":[49],"bound":[51],"algorithm":[52,118],"is":[53,77,97],"presented":[54],"integrates":[56],"parameter":[57],"structural":[59],"constraints":[60],"with":[61,70],"in":[63],"way":[65],"to":[66,72,119,124,137],"guarantee":[67],"global":[68,100],"optimality":[69],"respect":[71],"function.":[75],"It":[76],"an":[78,91],"any-time":[79],"procedure":[80],"because,":[81],"if":[82],"stopped,":[83],"provides":[85],"best":[87],"current":[88,134],"solution":[89],"estimation":[92],"about":[93],"how":[94],"far":[95],"solution.":[101],"We":[102],"show":[103],"empirically":[104],"advantages":[106],"constraints,":[112],"applicability":[115],"large":[120],"sets":[122],"(up":[123],"one":[125],"hundred":[126],"variables)":[127],"cannot":[129],"be":[130],"handled":[131],"by":[132],"other":[133],"(limited":[136],"around":[138],"30":[139],"variables).":[140]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":10},{"year":2014,"cited_by_count":14},{"year":2013,"cited_by_count":12},{"year":2012,"cited_by_count":13}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
