{"id":"https://openalex.org/W4307230603","doi":"https://doi.org/10.1109/tnnls.2022.3213518","title":"Bayesian Estimation of Inverted Beta Mixture Models With Extended Stochastic Variational Inference for Positive Vector Classification","display_name":"Bayesian Estimation of Inverted Beta Mixture Models With Extended Stochastic Variational Inference for Positive Vector Classification","publication_year":2022,"publication_date":"2022-11-03","ids":{"openalex":"https://openalex.org/W4307230603","doi":"https://doi.org/10.1109/tnnls.2022.3213518","pmid":"https://pubmed.ncbi.nlm.nih.gov/36279334"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3213518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3213518","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/A5004631861","display_name":"Yuping Lai","orcid":"https://orcid.org/0000-0002-3797-1228"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuping Lai","raw_affiliation_strings":["School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3797-1228","affiliations":[{"raw_affiliation_string":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103239389","display_name":"Wenbo Guan","orcid":"https://orcid.org/0000-0002-4645-6121"},"institutions":[{"id":"https://openalex.org/I4210099069","display_name":"Institute of Acoustics","ror":"https://ror.org/00v8rqv75","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210099069"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbo Guan","raw_affiliation_strings":["Institute of Acoustics, Beijing, CAS, China","Institute of Acoustics, CAS, Beijing, China","Institute of Information Engineering, CAS, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4645-6121","affiliations":[{"raw_affiliation_string":"Institute of Acoustics, Beijing, CAS, China","institution_ids":["https://openalex.org/I4210099069"]},{"raw_affiliation_string":"Institute of Acoustics, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210099069"]},{"raw_affiliation_string":"Institute of Information Engineering, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210156404"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012719173","display_name":"Lijuan Luo","orcid":"https://orcid.org/0000-0002-3702-372X"},"institutions":[{"id":"https://openalex.org/I11406153","display_name":"Shanghai International Studies University","ror":"https://ror.org/01bn89z48","country_code":"CN","type":"education","lineage":["https://openalex.org/I11406153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijuan Luo","raw_affiliation_strings":["School of Business and Management, Shanghai International Studies University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-3702-372X","affiliations":[{"raw_affiliation_string":"School of Business and Management, Shanghai International Studies University, Shanghai, China","institution_ids":["https://openalex.org/I11406153"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026927275","display_name":"Yanhui Guo","orcid":"https://orcid.org/0000-0003-1814-9682"},"institutions":[{"id":"https://openalex.org/I79884896","display_name":"University of Illinois at Springfield","ror":"https://ror.org/0126qma51","country_code":"US","type":"education","lineage":["https://openalex.org/I79884896"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanhui Guo","raw_affiliation_strings":["Department of Computer Science, University of Illinois Springfield, Springfield, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois Springfield, Springfield, IL, USA","institution_ids":["https://openalex.org/I79884896"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006796286","display_name":"Heping Song","orcid":"https://orcid.org/0000-0002-8583-2804"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heping Song","raw_affiliation_strings":["School of Computer Science and Communications Engineering, Jiangsu University, Zhenjiang, China"],"raw_orcid":"https://orcid.org/0000-0002-8583-2804","affiliations":[{"raw_affiliation_string":"School of Computer Science and Communications Engineering, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108055798","display_name":"Hongying Meng","orcid":"https://orcid.org/0000-0002-8836-1382"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hongying Meng","raw_affiliation_strings":["Electronic and Electrical Engineering Department, Brunel University London, Uxbridge, U.K"],"raw_orcid":"https://orcid.org/0000-0002-8836-1382","affiliations":[{"raw_affiliation_string":"Electronic and Electrical Engineering Department, Brunel University London, Uxbridge, U.K","institution_ids":["https://openalex.org/I59433898"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5004631861"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":1.2486,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.8323235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"35","issue":"5","first_page":"6948","last_page":"6962"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","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/T11901","display_name":"Bayesian Methods and Mixture Models","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/T12072","display_name":"Machine Learning and Algorithms","score":0.9990000128746033,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7218203544616699},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6480410099029541},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.5872548818588257},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5721203088760376},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5212648510932922},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.4961484372615814},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4939132332801819},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4656200110912323},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4549798369407654},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.45406243205070496},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4188064932823181},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36987370252609253},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27810993790626526},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2453436255455017},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09208068251609802}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7218203544616699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6480410099029541},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.5872548818588257},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5721203088760376},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5212648510932922},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.4961484372615814},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4939132332801819},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4656200110912323},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4549798369407654},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.45406243205070496},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4188064932823181},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36987370252609253},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27810993790626526},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2453436255455017},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09208068251609802},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2022.3213518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3213518","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:36279334","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36279334","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},{"id":"pmh:oai:bura.brunel.ac.uk:2438/25452","is_oa":false,"landing_page_url":"https://bura.brunel.ac.uk/handle/2438/25452","pdf_url":null,"source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1445160982","display_name":null,"funder_award_id":"2022RC16","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6101491803","display_name":null,"funder_award_id":"72101157","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6753774538","display_name":null,"funder_award_id":"62172193","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G77669080","display_name":null,"funder_award_id":"62272051","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/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W322150642","https://openalex.org/W1853714018","https://openalex.org/W1934021597","https://openalex.org/W1967203824","https://openalex.org/W2007413993","https://openalex.org/W2016155919","https://openalex.org/W2021052459","https://openalex.org/W2035893370","https://openalex.org/W2043699623","https://openalex.org/W2049633694","https://openalex.org/W2053571848","https://openalex.org/W2053822404","https://openalex.org/W2075798023","https://openalex.org/W2096118443","https://openalex.org/W2098162425","https://openalex.org/W2100537916","https://openalex.org/W2101222264","https://openalex.org/W2105499314","https://openalex.org/W2113526703","https://openalex.org/W2118020653","https://openalex.org/W2120475852","https://openalex.org/W2135631383","https://openalex.org/W2140321362","https://openalex.org/W2144245426","https://openalex.org/W2150755264","https://openalex.org/W2152594362","https://openalex.org/W2165072487","https://openalex.org/W2169658215","https://openalex.org/W2170902875","https://openalex.org/W2293857268","https://openalex.org/W2343999414","https://openalex.org/W2353323047","https://openalex.org/W2789389144","https://openalex.org/W2805560126","https://openalex.org/W2810809861","https://openalex.org/W2889379876","https://openalex.org/W2898045070","https://openalex.org/W2907421153","https://openalex.org/W2907500525","https://openalex.org/W2923501483","https://openalex.org/W2975042594","https://openalex.org/W2987333292","https://openalex.org/W2989699619","https://openalex.org/W3040389479","https://openalex.org/W3043450011","https://openalex.org/W3114441380","https://openalex.org/W3119160111","https://openalex.org/W3123287815","https://openalex.org/W3133568254","https://openalex.org/W3164653756","https://openalex.org/W3165205057","https://openalex.org/W3166668000","https://openalex.org/W3180417011","https://openalex.org/W3214669781","https://openalex.org/W4212863985","https://openalex.org/W4225502777","https://openalex.org/W4225693907","https://openalex.org/W4294562888","https://openalex.org/W6602473807","https://openalex.org/W6640231202","https://openalex.org/W6677157549","https://openalex.org/W6678215771","https://openalex.org/W6678804763","https://openalex.org/W6680380971","https://openalex.org/W6684391652","https://openalex.org/W6684489972","https://openalex.org/W6684578138","https://openalex.org/W6685053522","https://openalex.org/W6696357309","https://openalex.org/W6713018481","https://openalex.org/W6784170264"],"related_works":["https://openalex.org/W1975321310","https://openalex.org/W1952261593","https://openalex.org/W2014494654","https://openalex.org/W3130349901","https://openalex.org/W1579833936","https://openalex.org/W2107361128","https://openalex.org/W4286981651","https://openalex.org/W3197430630","https://openalex.org/W1563519935","https://openalex.org/W3152806123"],"abstract_inverted_index":{"The":[0,190],"finite":[1],"inverted":[2],"beta":[3],"mixture":[4],"model":[5],"(IBMM)":[6],"has":[7],"been":[8],"proven":[9],"to":[10,54,83,99,116,166,171,185],"be":[11,95,126,153],"efficient":[12,58,72],"in":[13,26,155,201],"modeling":[14],"positive":[15],"vectors.":[16],"Under":[17],"the":[18,23,30,34,49,62,80,85,89,100,105,108,118,138,145,169,187,196],"traditional":[19],"variational":[20,66],"inference":[21,39,67,73],"framework,":[22],"critical":[24],"challenge":[25],"Bayesian":[27,52],"estimation":[28],"of":[29,37,51,137,195],"IBMM":[31],"is":[32,43,183],"that":[33],"computational":[35],"cost":[36],"performing":[38],"with":[40,141,179],"large":[41,75],"datasets":[42],"prohibitively":[44],"expensive,":[45],"which":[46],"often":[47],"limits":[48],"use":[50,113],"approaches":[53],"small":[55],"datasets.":[56,76],"An":[57],"alternative":[59],"provided":[60],"by":[61],"recently":[63],"proposed":[64,197],"stochastic":[65,114,177],"(SVI)":[68],"framework":[69,82,110,140,151],"allows":[70],"for":[71],"on":[74],"Nevertheless,":[77],"when":[78],"using":[79],"SVI":[81,109,139,147],"address":[84,129],"non-Gaussian":[86,157],"statistical":[87,158],"models,":[88],"evidence":[90],"lower":[91,168,188],"bound":[92],"(ELBO)":[93],"cannot":[94,111,125],"explicitly":[96],"calculated":[97],"due":[98],"intractable":[101,173],"moment":[102,174],"computation.":[103],"Therefore,":[104],"algorithm":[106],"under":[107],"directly":[112],"optimization":[115,178],"optimize":[117,186],"ELBO,":[119],"and":[120,193],"an":[121,134],"analytically":[122],"tractable":[123],"solution":[124],"derived.":[127],"To":[128],"this":[130],"problem,":[131],"we":[132],"propose":[133],"extended":[135,146],"version":[136],"more":[142],"flexibility,":[143],"namely,":[144],"(ESVI)":[148],"framework.":[149],"This":[150],"can":[152],"used":[154,184],"many":[156],"models.":[159],"First,":[160],"some":[161],"approximation":[162],"strategies":[163],"are":[164,199],"applied":[165],"further":[167],"ELBO":[170],"avoid":[172],"calculations.":[175],"Then,":[176],"noisy":[180],"natural":[181],"gradients":[182],"bound.":[189],"excellent":[191],"performance":[192],"effectiveness":[194],"method":[198],"verified":[200],"real":[202],"data":[203],"evaluation.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}