{"id":"https://openalex.org/W2034315836","doi":"https://doi.org/10.1109/tpami.2014.2315802","title":"The Supervised Hierarchical Dirichlet Process","display_name":"The Supervised Hierarchical Dirichlet Process","publication_year":2014,"publication_date":"2014-04-07","ids":{"openalex":"https://openalex.org/W2034315836","doi":"https://doi.org/10.1109/tpami.2014.2315802","mag":"2034315836","pmid":"https://pubmed.ncbi.nlm.nih.gov/26353239"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2014.2315802","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2014.2315802","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1412.5236","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029197877","display_name":"Andrew M. Dai","orcid":"https://orcid.org/0000-0002-7112-8277"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrew M. Dai","raw_affiliation_strings":["Google Inc., 1600 Amphitheatre Parkway, Mountain View, CA","[Google Inc., 1600 Amphitheatre Parkway, Mountain View, CA]"],"affiliations":[{"raw_affiliation_string":"Google Inc., 1600 Amphitheatre Parkway, Mountain View, CA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"[Google Inc., 1600 Amphitheatre Parkway, Mountain View, CA]","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007901825","display_name":"Amos Storkey","orcid":"https://orcid.org/0000-0002-8100-506X"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Amos J. Storkey","raw_affiliation_strings":["Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, United Kingdom","[Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, United Kingdom]"],"affiliations":[{"raw_affiliation_string":"Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, United Kingdom","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"[Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, United Kingdom]","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029197877"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":5.0921,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.95389313,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"37","issue":"2","first_page":"243","last_page":"255"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9987999796867371,"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":0.9987999796867371,"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/computer-science","display_name":"Computer science","score":0.6519205570220947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6319110989570618},{"id":"https://openalex.org/keywords/hierarchical-dirichlet-process","display_name":"Hierarchical Dirichlet process","score":0.5788697004318237},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.5321753621101379},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5093375444412231},{"id":"https://openalex.org/keywords/dirichlet-process","display_name":"Dirichlet process","score":0.439314603805542},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4304085075855255},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4139420986175537},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.1660226285457611},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.12152275443077087}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6519205570220947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6319110989570618},{"id":"https://openalex.org/C141318989","wikidata":"https://www.wikidata.org/wiki/Q5753066","display_name":"Hierarchical Dirichlet process","level":4,"score":0.5788697004318237},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.5321753621101379},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5093375444412231},{"id":"https://openalex.org/C2781280628","wikidata":"https://www.wikidata.org/wiki/Q5280766","display_name":"Dirichlet process","level":3,"score":0.439314603805542},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4304085075855255},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4139420986175537},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.1660226285457611},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.12152275443077087},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tpami.2014.2315802","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2014.2315802","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:26353239","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26353239","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 pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:arXiv.org:1412.5236","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1412.5236","pdf_url":"https://arxiv.org/pdf/1412.5236","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1412.5236","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1412.5236","pdf_url":"https://arxiv.org/pdf/1412.5236","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1581986412","https://openalex.org/W1746819321","https://openalex.org/W1880262756","https://openalex.org/W1915058860","https://openalex.org/W1947594277","https://openalex.org/W1967687583","https://openalex.org/W1969486090","https://openalex.org/W2001082470","https://openalex.org/W2010291682","https://openalex.org/W2035983506","https://openalex.org/W2055341013","https://openalex.org/W2058849009","https://openalex.org/W2069429561","https://openalex.org/W2080972498","https://openalex.org/W2093223772","https://openalex.org/W2098062695","https://openalex.org/W2101101940","https://openalex.org/W2112121851","https://openalex.org/W2140124448","https://openalex.org/W2148534890","https://openalex.org/W2154036191","https://openalex.org/W2158266063","https://openalex.org/W2161050705","https://openalex.org/W2161353674","https://openalex.org/W2163455955","https://openalex.org/W2181470043","https://openalex.org/W2949169239","https://openalex.org/W2949205689","https://openalex.org/W2952186591","https://openalex.org/W2952505044","https://openalex.org/W3005335434","https://openalex.org/W4211049957","https://openalex.org/W4231510805","https://openalex.org/W4237780050","https://openalex.org/W4249731213","https://openalex.org/W4252381709","https://openalex.org/W6634664379","https://openalex.org/W6639619044","https://openalex.org/W6639973174","https://openalex.org/W6640753970","https://openalex.org/W6664418264","https://openalex.org/W6674735981","https://openalex.org/W6676959145","https://openalex.org/W6682567057","https://openalex.org/W6683847445","https://openalex.org/W6834357723"],"related_works":["https://openalex.org/W2954539699","https://openalex.org/W2059879108","https://openalex.org/W2048766621","https://openalex.org/W3142820572","https://openalex.org/W4381683374","https://openalex.org/W2803512450","https://openalex.org/W2097627380","https://openalex.org/W2939843948","https://openalex.org/W2053909857","https://openalex.org/W1989637290"],"abstract_inverted_index":{"We":[0,31,51],"propose":[1],"the":[2,13,33,44,71,76,118,121,133,149,154],"supervised":[3,45,108],"hierarchical":[4,97],"Dirichlet":[5,47,72,77,98],"process":[6,99],"(sHDP),":[7],"a":[8,17,22,114],"nonparametric":[9,66],"generative":[10],"model":[11],"for":[12,39,142],"joint":[14],"distribution":[15],"of":[16,19,117,132],"group":[18,150],"observations":[20],"and":[21,60,152],"response":[23],"variable":[24],"directly":[25],"associated":[26],"with":[27,35,110],"that":[28,128],"whole":[29],"group.":[30,159],"compare":[32],"sHDP":[34,136],"another":[36],"leading":[37],"method":[38,54],"regression":[40,63,67],"on":[41,55,70,120],"grouped":[42,111,122],"data,":[43],"latent":[46],"allocation":[48],"(sLDA)":[49],"model.":[50],"evaluate":[52],"our":[53],"two":[56,61],"real-world":[57,62],"classification":[58],"problems":[59,109],"problems.":[64],"Bayesian":[65],"models":[68,80,87],"based":[69],"process,":[73],"such":[74],"as":[75],"process-generalised":[78],"linear":[79],"(DP-GLM)":[81],"have":[82,102],"previously":[83],"been":[84],"explored;":[85],"these":[86],"allow":[88],"flexibility":[89],"in":[90,107,125],"modelling":[91],"nonlinear":[92],"relationships.":[93],"However,":[94],"until":[95],"now,":[96],"(HDP)":[100],"mixtures":[101],"not":[103,130],"seen":[104],"significant":[105],"use":[106],"data":[112,123],"since":[113],"straightforward":[115],"application":[116],"HDP":[119],"results":[124],"learnt":[126,146],"clusters":[127,143],"are":[129],"predictive":[131],"responses.":[134],"The":[135],"solves":[137],"this":[138],"problem":[139],"by":[140],"allowing":[141],"to":[144,157],"be":[145],"jointly":[147],"from":[148,153],"structure":[151],"label":[155],"assigned":[156],"each":[158]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
