{"id":"https://openalex.org/W3094604059","doi":"https://doi.org/10.1145/3340531.3411971","title":"Deep Generative Positive-Unlabeled Learning under Selection Bias","display_name":"Deep Generative Positive-Unlabeled Learning under Selection Bias","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3094604059","doi":"https://doi.org/10.1145/3340531.3411971","mag":"3094604059"},"language":"en","primary_location":{"id":"doi:10.1145/3340531.3411971","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3411971","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information & Knowledge Management","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/A5065601135","display_name":"Byeonghu Na","orcid":"https://orcid.org/0000-0003-3463-2674"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Byeonghu Na","raw_affiliation_strings":["KAIST, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"KAIST, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076443181","display_name":"Hyemi Kim","orcid":"https://orcid.org/0000-0003-4713-4658"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyemi Kim","raw_affiliation_strings":["KAIST, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"KAIST, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025711483","display_name":"Kyungwoo Song","orcid":"https://orcid.org/0000-0003-0082-4280"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyungwoo Song","raw_affiliation_strings":["KAIST, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"KAIST, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013918979","display_name":"Weonyoung Joo","orcid":"https://orcid.org/0000-0003-3544-6961"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Weonyoung Joo","raw_affiliation_strings":["KAIST, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"KAIST, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044632351","display_name":"Yoon-Yeong Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yoon-Yeong Kim","raw_affiliation_strings":["KAIST, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"KAIST, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017589963","display_name":"Il\u2010Chul Moon","orcid":"https://orcid.org/0000-0002-1798-1306"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Il-Chul Moon","raw_affiliation_strings":["KAIST, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"KAIST, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5065601135"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":1.3256,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.85035842,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1155","last_page":"1164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9997000098228455,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9997000098228455,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9932000041007996,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9847000241279602,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.682891845703125},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6822823286056519},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6584876179695129},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6559804677963257},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.6294721364974976},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5555656552314758},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4933847486972809},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47954508662223816},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46396151185035706},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4457642138004303},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.4352586269378662}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.682891845703125},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6822823286056519},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6584876179695129},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6559804677963257},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.6294721364974976},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5555656552314758},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4933847486972809},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47954508662223816},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46396151185035706},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4457642138004303},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.4352586269378662},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3340531.3411971","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3411971","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5602054466","display_name":null,"funder_award_id":"NRF-2019M3F2A1072239","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1959608418","https://openalex.org/W2096635897","https://openalex.org/W2101029276","https://openalex.org/W2123958887","https://openalex.org/W2124431629","https://openalex.org/W2191189641","https://openalex.org/W2593576259","https://openalex.org/W2730106296","https://openalex.org/W2770173563","https://openalex.org/W2788085070","https://openalex.org/W2799709780","https://openalex.org/W2808199275","https://openalex.org/W2895752198","https://openalex.org/W2912500072","https://openalex.org/W2924476266","https://openalex.org/W2962739339","https://openalex.org/W2963341628","https://openalex.org/W2963875483","https://openalex.org/W2964121744","https://openalex.org/W2995354853","https://openalex.org/W3104154887"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W2967848559","https://openalex.org/W4299831724","https://openalex.org/W4283803360"],"abstract_inverted_index":{"Learning":[0],"in":[1,8,43,100],"the":[2,28,36,49,56,62,67,81,91,101,106,132,141,149,156,165,171,179],"positive-unlabeled":[3],"(PU)":[4],"setting":[5],"is":[6,31,48,88,109,158,167,181],"prevalent":[7],"real":[9,37],"world":[10,38],"applications.":[11],"Many":[12],"previous":[13],"works":[14],"depend":[15],"upon":[16],"theSelected":[17],"Completely":[18],"At":[19],"Random":[20],"(SCAR)":[21],"assumption":[22,30],"to":[23,35,40,79,115,134,190],"utilize":[24],"unlabeled":[25],"data,":[26],"but":[27],"SCAR":[29,57,68,150,172],"not":[32,98],"often":[33],"applicable":[34],"due":[39,189],"selection":[41,161,193],"bias":[42,162],"label":[44],"observations.":[45,102],"This":[46],"paper":[47],"first":[50],"generative":[51],"PU":[52,63,77,85,94,137],"learning":[53],"model":[54,133],"without":[55,66,148],"assumption.":[58,151,173],"Specifically,":[59],"we":[60,71,104],"derive":[61],"risk":[64,86],"function":[65,87,92],"assumption,":[69],"and":[70,147,164],"generate":[72,121,135],"a":[73,110],"set":[74],"of":[75,112],"virtual":[76,136],"examples":[78],"train":[80],"classifier.":[82],"Although":[83],"our":[84],"more":[89],"generalizable,":[90],"requires":[93],"instances":[95,188],"that":[96,120,155,178],"do":[97],"exist":[99],"Therefore,":[103],"introduce":[105],"VAE-PU,":[107],"which":[108],"variant":[111],"variational":[113],"autoencoders":[114],"separate":[116],"two":[117],"latent":[118,129],"variables":[119],"either":[122],"features":[123],"or":[124],"observation":[125],"indicators.":[126],"The":[127,152,174],"separated":[128],"information":[130],"enables":[131],"instances.":[138],"We":[139],"test":[140],"VAE-PU":[142,157,166,180],"on":[143,192],"benchmark":[144],"datasets":[145],"with":[146],"results":[153,175],"indicate":[154],"superior":[159],"when":[160,183],"exists,":[163],"also":[168,176],"competent":[169],"under":[170],"emphasize":[177],"effective":[182],"there":[184],"are":[185],"few":[186],"positive-labeled":[187],"modeling":[191],"bias.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}