{"id":"https://openalex.org/W2122110645","doi":"https://doi.org/10.1145/2556195.2556238","title":"Nonparametric bayesian upstream supervised multi-modal topic models","display_name":"Nonparametric bayesian upstream supervised multi-modal topic models","publication_year":2014,"publication_date":"2014-02-18","ids":{"openalex":"https://openalex.org/W2122110645","doi":"https://doi.org/10.1145/2556195.2556238","mag":"2122110645"},"language":"en","primary_location":{"id":"doi:10.1145/2556195.2556238","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2556195.2556238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM international conference on Web search and data mining","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/A5048686150","display_name":"Renjie Liao","orcid":"https://orcid.org/0009-0001-1660-9959"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Renjie Liao","raw_affiliation_strings":["The Chinese University of Hong Kong, HongKong, Hong Kong","The Chinese University of Hong Kong, HongKong, Hong Kong#TAB#"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, HongKong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, HongKong, Hong Kong#TAB#","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100606995","display_name":"Jun Zhu","orcid":"https://orcid.org/0000-0002-6254-2388"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032405950","display_name":"Zengchang Qin","orcid":"https://orcid.org/0000-0002-8084-6721"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zengchang Qin","raw_affiliation_strings":["Beihang University, Beijing, China","BeiHang University, BeiJing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"BeiHang University, BeiJing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048686150"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":1.4828,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.86361063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"493","last_page":"502"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9944999814033508,"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"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9944999814033508,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9944000244140625,"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"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9908999800682068,"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/computer-science","display_name":"Computer science","score":0.7169379591941833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6478521823883057},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.630010724067688},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.618954062461853},{"id":"https://openalex.org/keywords/dirichlet-process","display_name":"Dirichlet process","score":0.6116642355918884},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5607476234436035},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5362460017204285},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.47430944442749023},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.4575977921485901},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.446972519159317},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4252970516681671},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37239307165145874},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34873828291893005},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.2356409728527069},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14588940143585205},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11227211356163025}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7169379591941833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6478521823883057},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.630010724067688},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.618954062461853},{"id":"https://openalex.org/C2781280628","wikidata":"https://www.wikidata.org/wiki/Q5280766","display_name":"Dirichlet process","level":3,"score":0.6116642355918884},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5607476234436035},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5362460017204285},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.47430944442749023},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.4575977921485901},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.446972519159317},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4252970516681671},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37239307165145874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34873828291893005},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.2356409728527069},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14588940143585205},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11227211356163025},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum 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},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2556195.2556238","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2556195.2556238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM international conference on Web search and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.434.3839","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.434.3839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ml-thu.net/~jun/pub/p493-liao-zhu-qin.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W42729272","https://openalex.org/W242703795","https://openalex.org/W1484654248","https://openalex.org/W1495177430","https://openalex.org/W1516111018","https://openalex.org/W1532737361","https://openalex.org/W1666447063","https://openalex.org/W1676494021","https://openalex.org/W1746819321","https://openalex.org/W1877469910","https://openalex.org/W1880262756","https://openalex.org/W1938896346","https://openalex.org/W1972112592","https://openalex.org/W2004646046","https://openalex.org/W2020842694","https://openalex.org/W2043696649","https://openalex.org/W2064797228","https://openalex.org/W2065594991","https://openalex.org/W2069429561","https://openalex.org/W2071207147","https://openalex.org/W2079666190","https://openalex.org/W2089484716","https://openalex.org/W2098062695","https://openalex.org/W2100476178","https://openalex.org/W2106277773","https://openalex.org/W2107034620","https://openalex.org/W2122695597","https://openalex.org/W2123111158","https://openalex.org/W2125238156","https://openalex.org/W2127411609","https://openalex.org/W2128925311","https://openalex.org/W2133568543","https://openalex.org/W2148212498","https://openalex.org/W2151103935","https://openalex.org/W2151800797","https://openalex.org/W2151967501","https://openalex.org/W2156336347","https://openalex.org/W2156637418","https://openalex.org/W2157381218","https://openalex.org/W2158266063","https://openalex.org/W2536305071","https://openalex.org/W2963210425","https://openalex.org/W2963214665","https://openalex.org/W3099640513","https://openalex.org/W4211049957","https://openalex.org/W4251504464","https://openalex.org/W6630475436","https://openalex.org/W6632034549","https://openalex.org/W6674735981","https://openalex.org/W6678852649","https://openalex.org/W6682569104","https://openalex.org/W7033535967"],"related_works":["https://openalex.org/W4243114048","https://openalex.org/W4237896776","https://openalex.org/W4231665652","https://openalex.org/W2000242494","https://openalex.org/W4296826658","https://openalex.org/W1837630526","https://openalex.org/W2529605301","https://openalex.org/W2335589441","https://openalex.org/W2031917313","https://openalex.org/W4214574858"],"abstract_inverted_index":{"Learning":[0],"with":[1,150],"multi-modal":[2,36,45],"data":[3,53,89],"is":[4],"at":[5],"the":[6,49,65,110,114],"core":[7],"of":[8,52,78,104,113,116],"many":[9],"multimedia":[10],"applications,":[11],"such":[12],"as":[13],"cross-modal":[14],"retrieval":[15],"and":[16,59,76,98,124,137],"image":[17],"annotation.":[18],"In":[19],"this":[20],"paper,":[21],"we":[22],"present":[23],"a":[24,41],"nonparametric":[25,43],"Bayesian":[26,44],"approach":[27],"to":[28,47],"learning":[29,103,121],"upstream":[30,72,129],"supervised":[31,73],"topic":[32],"models":[33],"for":[34,95],"analyzing":[35],"data.":[37],"Our":[38],"model":[39,108],"develops":[40],"compound":[42],"prior":[46],"describe":[48],"correlation":[50],"structure":[51,102,120],"both":[54],"within":[55],"each":[56],"individual":[57],"modality":[58],"between":[60],"different":[61],"modalities.":[62],"It":[63],"extends":[64],"hierarchical":[66],"Dirichlet":[67],"process":[68,83],"(HDP)":[69],"through":[70],"incorporating":[71],"response":[74],"variables":[75],"values":[77],"latent":[79],"functions":[80],"under":[81],"Gaussian":[82],"(GP).":[84],"Upstream":[85],"responses":[86],"shared":[87],"by":[88],"from":[90,118,122,128],"multiple":[91],"modalities":[92],"are":[93],"beneficial":[94],"discriminatively":[96],"training":[97],"GP":[99,123],"allows":[100],"flexible":[101],"correlations.":[105],"Hence,":[106],"our":[107],"inherits":[109],"automatic":[111],"determination":[112],"number":[115],"topics":[117],"HDP,":[119],"enhanced":[125],"predictive":[126],"capacity":[127],"supervision.":[130],"We":[131],"also":[132],"provide":[133],"efficient":[134],"variational":[135],"inference":[136],"prediction":[138],"algorithms.":[139],"Empirical":[140],"studies":[141],"demonstrate":[142],"superior":[143],"performances":[144],"on":[145],"several":[146],"benchmark":[147],"datasets":[148],"compared":[149],"previous":[151],"competitors.":[152]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}