{"id":"https://openalex.org/W2985793995","doi":"https://doi.org/10.1109/tii.2019.2903718","title":"Partial Bayesian Co-training for Virtual Metrology","display_name":"Partial Bayesian Co-training for Virtual Metrology","publication_year":2019,"publication_date":"2019-03-07","ids":{"openalex":"https://openalex.org/W2985793995","doi":"https://doi.org/10.1109/tii.2019.2903718","mag":"2985793995"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2019.2903718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2019.2903718","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-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/A5057715671","display_name":"Manh Cuong Nguyen","orcid":"https://orcid.org/0000-0002-6342-1393"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Cuong Manh Nguyen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353869","display_name":"Xin Li","orcid":"https://orcid.org/0000-0002-4510-2436"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]},{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG","US"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, USA","Singapore Institute of Manufacturing Technology, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, USA","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Singapore Institute of Manufacturing Technology, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039038157","display_name":"R. D. Blanton","orcid":"https://orcid.org/0000-0001-6108-2925"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ronald DeShawn Blanton","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022516253","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0002-3919-2658"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]},{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG","US"],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, USA","Singapore Institute of Manufacturing Technology, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, USA","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Singapore Institute of Manufacturing Technology, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057715671"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":2.3929,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.90631405,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"16","issue":"5","first_page":"2937","last_page":"2945"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/overfitting","display_name":"Overfitting","score":0.92292320728302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6871166229248047},{"id":"https://openalex.org/keywords/co-training","display_name":"Co-training","score":0.6385804414749146},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6156196594238281},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.59353107213974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5906103849411011},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5556547045707703},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.5065828561782837},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.49187135696411133},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4598655700683594},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4536615312099457},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44717830419540405},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.42640557885169983},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.41884222626686096},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.20153489708900452},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11884570121765137},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.08628776669502258}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.92292320728302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6871166229248047},{"id":"https://openalex.org/C2776959682","wikidata":"https://www.wikidata.org/wiki/Q17005296","display_name":"Co-training","level":3,"score":0.6385804414749146},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6156196594238281},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.59353107213974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5906103849411011},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5556547045707703},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.5065828561782837},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.49187135696411133},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4598655700683594},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4536615312099457},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44717830419540405},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.42640557885169983},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.41884222626686096},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.20153489708900452},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11884570121765137},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.08628776669502258},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2019.2903718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2019.2903718","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G2326946035","display_name":null,"funder_award_id":"U15-E-011SV","funder_id":"https://openalex.org/F4320320696","funder_display_name":"Agency for Science, Technology and Research"}],"funders":[{"id":"https://openalex.org/F4320320696","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1484030678","https://openalex.org/W1579717263","https://openalex.org/W1663973292","https://openalex.org/W1670132599","https://openalex.org/W1824737917","https://openalex.org/W1939743097","https://openalex.org/W2000304567","https://openalex.org/W2009086942","https://openalex.org/W2014915963","https://openalex.org/W2032058792","https://openalex.org/W2035983272","https://openalex.org/W2048679005","https://openalex.org/W2053430356","https://openalex.org/W2070963892","https://openalex.org/W2075852334","https://openalex.org/W2106485576","https://openalex.org/W2113242816","https://openalex.org/W2117898853","https://openalex.org/W2128614648","https://openalex.org/W2133348086","https://openalex.org/W2135046866","https://openalex.org/W2139430280","https://openalex.org/W2140676093","https://openalex.org/W2175133354","https://openalex.org/W2215421138","https://openalex.org/W2226450201","https://openalex.org/W2280751535","https://openalex.org/W2465146196","https://openalex.org/W2508380041","https://openalex.org/W2527556222","https://openalex.org/W2597121862","https://openalex.org/W2726451741","https://openalex.org/W2783646838","https://openalex.org/W2883783597","https://openalex.org/W4236314258","https://openalex.org/W6602211964","https://openalex.org/W6636883489","https://openalex.org/W6677329495","https://openalex.org/W6679131053","https://openalex.org/W6679629151","https://openalex.org/W6680161228","https://openalex.org/W6685191041","https://openalex.org/W6688152027"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W1975561281"],"abstract_inverted_index":{"Building":[0],"accurate":[1],"regression":[2],"models":[3],"using":[4],"limited":[5],"data":[6,13,27,32,121],"is":[7,103,129,138],"a":[8,20,52,71,117,126,139,143],"challenging":[9],"problem":[10,24],"in":[11],"manufacturing":[12,109],"analysis.":[14],"In":[15,35],"this":[16,48],"paper,":[17],"we":[18,50],"study":[19],"particular":[21],"semisupervised":[22],"learning":[23,40],"where":[25],"labeled":[26,120],"are":[28,33,42],"limited,":[29],"while":[30],"unlabeled":[31],"plentiful.":[34],"these":[36],"conditions,":[37],"conventional":[38],"single-view":[39],"methods":[41],"prone":[43],"to":[44,69,83,96,124,142],"overfitting.":[45],"To":[46],"tackle":[47],"problem,":[49],"develop":[51],"novel":[53],"co-training":[54,59],"technique,":[55],"namely":[56],"partial":[57,72,81],"Bayesian":[58],"(PBCT).":[60],"PBCT":[61,89,136],"scales":[62],"down":[63],"the":[64,80,85,135],"original":[65],"set":[66],"of":[67,119,146],"features":[68],"create":[70],"view,":[73],"and":[74],"then":[75],"exploit":[76],"side":[77],"information":[78],"from":[79],"view":[82],"enhance":[84,97],"complete":[86],"model.":[87],"The":[88,100,111],"model":[90,98,137],"also":[91],"allows":[92],"integrating":[93],"domain":[94],"knowledge":[95],"accuracy.":[99],"proposed":[101],"method":[102],"validated":[104],"with":[105],"experiments":[106],"on":[107],"industrial":[108],"data.":[110],"experimental":[112],"results":[113],"show":[114],"that":[115,134],"under":[116],"reduction":[118],"by":[122],"up":[123],"50%,":[125],"robust":[127],"estimation":[128],"still":[130],"attainable.":[131],"This":[132],"suggests":[133],"promising":[140],"solution":[141],"broad":[144],"spectrum":[145],"applications.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
