{"id":"https://openalex.org/W2746760564","doi":"https://doi.org/10.1109/tnnls.2017.2727065","title":"Adaboost-LLP: A Boosting Method for Learning With Label Proportions","display_name":"Adaboost-LLP: A Boosting Method for Learning With Label Proportions","publication_year":2017,"publication_date":"2017-08-15","ids":{"openalex":"https://openalex.org/W2746760564","doi":"https://doi.org/10.1109/tnnls.2017.2727065","mag":"2746760564","pmid":"https://pubmed.ncbi.nlm.nih.gov/28816675"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2017.2727065","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2727065","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5013051763","display_name":"Zhiquan Qi","orcid":"https://orcid.org/0000-0001-9289-9110"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiquan Qi","raw_affiliation_strings":["Key Laboratory of Big Data Mining and Knowledge Management, Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9289-9110","affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data Mining and Knowledge Management, Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210096250","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103151002","display_name":"Fan Meng","orcid":"https://orcid.org/0000-0002-4818-7009"},"institutions":[{"id":"https://openalex.org/I137867983","display_name":"Central University of Finance and Economics","ror":"https://ror.org/008e3hf02","country_code":"CN","type":"education","lineage":["https://openalex.org/I137867983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Meng","raw_affiliation_strings":["School of Management Science and Engineering, Central University of Finance and Economics, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Management Science and Engineering, Central University of Finance and Economics, Beijing, China","institution_ids":["https://openalex.org/I137867983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032861309","display_name":"Yingjie Tian","orcid":"https://orcid.org/0000-0002-4675-0398"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingjie Tian","raw_affiliation_strings":["Key Laboratory of Big Data Mining and Knowledge Management, Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4675-0398","affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data Mining and Knowledge Management, Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210096250","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108615648","display_name":"Lingfeng Niu","orcid":"https://orcid.org/0000-0002-5827-8449"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingfeng Niu","raw_affiliation_strings":["Key Laboratory of Big Data Mining and Knowledge Management, Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5827-8449","affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data Mining and Knowledge Management, Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210096250","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113542097","display_name":"Yong Shi","orcid":"https://orcid.org/0000-0001-7974-1079"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Shi","raw_affiliation_strings":["Key Laboratory of Big Data Mining and Knowledge Management, Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data Mining and Knowledge Management, Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210096250","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100364127","display_name":"Peng Zhang","orcid":"https://orcid.org/0000-0002-3879-5860"},"institutions":[{"id":"https://openalex.org/I4210090985","display_name":"Zhejiang Financial College","ror":"https://ror.org/00deghz86","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210090985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Zhang","raw_affiliation_strings":["Ant Financial Services Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Financial Services Group, Hangzhou, China","institution_ids":["https://openalex.org/I4210090985"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.7882,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.94757562,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"29","issue":"8","first_page":"3548","last_page":"3559"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9970999956130981,"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":0.9970999956130981,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9952999949455261,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9890000224113464,"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/boosting","display_name":"Boosting (machine learning)","score":0.8802875280380249},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.7882366180419922},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5638588070869446},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48995891213417053},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4515690505504608},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38626596331596375},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.0628838837146759}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8802875280380249},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.7882366180419922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5638588070869446},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48995891213417053},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4515690505504608},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38626596331596375},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0628838837146759}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2017.2727065","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2727065","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:28816675","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28816675","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2326598571","display_name":null,"funder_award_id":"61402429","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G248771173","display_name":"\u9886\u57df\u77e5\u8bc6\u9a71\u52a8\u4e0b\u7684\u91d1\u878d\u6570\u636e\u6d41\u5f02\u5e38\u6a21\u5f0f\u7814\u7a76","funder_award_id":"71401188","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5264941446","display_name":null,"funder_award_id":"91546201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5959469421","display_name":"\u53ef\u62d3\u652f\u6301\u5411\u91cf\u673a\u7406\u8bba\u3001\u65b9\u6cd5\u4e0e\u5e94\u7528\u7814\u7a76","funder_award_id":"61472390","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G645463129","display_name":"\u5927\u6570\u636e\u73af\u5883\u4e0b\u7684\u7ba1\u7406\u51b3\u7b56\u521b\u65b0\u7814\u7a76","funder_award_id":"71331005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6771848077","display_name":"\u77e5\u8bc6\u9a71\u52a8\u7684\u652f\u6301\u5411\u91cf\u673a\u7406\u8bba\u3001\u7b97\u6cd5\u4e0e\u5e94\u7528\u7814\u7a76","funder_award_id":"11271361","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W7903576","https://openalex.org/W15704962","https://openalex.org/W1524068846","https://openalex.org/W1547172162","https://openalex.org/W1563294799","https://openalex.org/W1564684449","https://openalex.org/W1565746575","https://openalex.org/W1607038179","https://openalex.org/W1790119552","https://openalex.org/W1961428732","https://openalex.org/W1972230955","https://openalex.org/W1976190508","https://openalex.org/W2004236981","https://openalex.org/W2027266161","https://openalex.org/W2028704235","https://openalex.org/W2042184006","https://openalex.org/W2063438554","https://openalex.org/W2064460620","https://openalex.org/W2065218422","https://openalex.org/W2066446909","https://openalex.org/W2067624665","https://openalex.org/W2077484223","https://openalex.org/W2082741089","https://openalex.org/W2090089568","https://openalex.org/W2098986246","https://openalex.org/W2103284199","https://openalex.org/W2107634464","https://openalex.org/W2108094618","https://openalex.org/W2108263314","https://openalex.org/W2108745803","https://openalex.org/W2110119381","https://openalex.org/W2114396536","https://openalex.org/W2115240329","https://openalex.org/W2117426363","https://openalex.org/W2120742448","https://openalex.org/W2128532956","https://openalex.org/W2135533176","https://openalex.org/W2149648623","https://openalex.org/W2154318594","https://openalex.org/W2158681777","https://openalex.org/W2163811596","https://openalex.org/W2166010828","https://openalex.org/W2185563688","https://openalex.org/W2219738499","https://openalex.org/W2222844749","https://openalex.org/W2407981807","https://openalex.org/W2606082972","https://openalex.org/W2953144970","https://openalex.org/W2964324211","https://openalex.org/W2997519153","https://openalex.org/W6636455955","https://openalex.org/W6638276564","https://openalex.org/W6640970874","https://openalex.org/W6666760051","https://openalex.org/W6676245398","https://openalex.org/W6676249281","https://openalex.org/W6676896291","https://openalex.org/W6676992119","https://openalex.org/W6677462325","https://openalex.org/W6677492792","https://openalex.org/W6680102115","https://openalex.org/W6683033130","https://openalex.org/W6683235360","https://openalex.org/W6684369376","https://openalex.org/W6684436126","https://openalex.org/W6689149156"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W1538046993","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W2385662756","https://openalex.org/W2585372724","https://openalex.org/W2241444561","https://openalex.org/W1502951582"],"abstract_inverted_index":{"How":[0],"to":[1,29,130],"solve":[2],"the":[3,16,32,56,61,77,107,142],"classification":[4],"problem":[5,34],"with":[6,31,35,111],"only":[7],"label":[8,36],"proportions":[9,37],"has":[10],"recently":[11],"drawn":[12],"increasing":[13],"attention":[14],"in":[15,145],"machine":[17],"learning":[18,27,33,86],"field.":[19],"In":[20,39],"this":[21],"paper,":[22],"we":[23,41,81],"propose":[24,82],"an":[25],"ensemble":[26],"strategy":[28],"deal":[30],"(LLP).":[38],"detail,":[40],"first":[42],"give":[43],"a":[44,69,83,132],"loss":[45],"function":[46],"based":[47],"on":[48,103],"different":[49],"weights":[50],"for":[51,88],"LLP,":[52],"and":[53,120,148],"then":[54],"construct":[55],"corresponding":[57],"weak":[58,123],"classifier,":[59],"at":[60,106],"same":[62,108],"time,":[63,109],"estimate":[64],"its":[65],"conditional":[66],"probabilities":[67],"by":[68,75],"standard":[70],"logistic":[71],"function.":[72],"At":[73],"last,":[74],"introducing":[76],"maximum":[78],"likelihood":[79],"estimation,":[80],"new":[84],"anyboost":[85],"system":[87],"LLP":[89],"(called":[90],"Adaboost-LLP).":[91],"Unlike":[92],"traditional":[93],"methods,":[94],"our":[95,139],"method":[96,140],"does":[97],"not":[98],"make":[99],"any":[100],"restrictive":[101],"assumptions":[102],"training":[104,149],"set;":[105],"compared":[110],"alter-":[112],"SVM,":[113],"Adaboost-LLP":[114],"exploits":[115],"more":[116],"extra":[117],"weight":[118],"information":[119],"uses":[121],"multiple":[122],"classifiers":[124],"that":[125,138],"can":[126],"be":[127],"solved":[128],"efficiently":[129],"combine":[131],"strong":[133],"classifier.":[134],"All":[135],"experiments":[136],"show":[137],"outperforms":[141],"existing":[143],"methods":[144],"both":[146],"accuracy":[147],"time.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}