{"id":"https://openalex.org/W4392251929","doi":"https://doi.org/10.1109/tmm.2024.3369862","title":"Wasserstein Embedding Learning for Deep Clustering: A Generative Approach","display_name":"Wasserstein Embedding Learning for Deep Clustering: A Generative Approach","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4392251929","doi":"https://doi.org/10.1109/tmm.2024.3369862"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2024.3369862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2024.3369862","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-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/A5001505336","display_name":"Jinyu Cai","orcid":"https://orcid.org/0000-0003-2241-2754"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]},{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyu Cai","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fujian, China","The Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2241-2754","affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fujian, China","institution_ids":["https://openalex.org/I80947539"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100755782","display_name":"Yunhe Zhang","orcid":"https://orcid.org/0000-0002-8080-3828"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]},{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhe Zhang","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fujian, China","The Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-8080-3828","affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fujian, China","institution_ids":["https://openalex.org/I80947539"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100604225","display_name":"Shiping Wang","orcid":"https://orcid.org/0000-0001-5195-9682"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]},{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiping Wang","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fujian, China","The Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-5195-9682","affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fujian, China","institution_ids":["https://openalex.org/I80947539"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065547403","display_name":"Jicong Fan","orcid":"https://orcid.org/0000-0001-9665-0355"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jicong Fan","raw_affiliation_strings":["The Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-9665-0355","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100643723","display_name":"Wenzhong Guo","orcid":"https://orcid.org/0000-0003-4118-8823"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]},{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzhong Guo","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fujian, China","The Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-4118-8823","affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fujian, China","institution_ids":["https://openalex.org/I80947539"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.2598,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.98698885,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"26","issue":null,"first_page":"7567","last_page":"7580"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9991999864578247,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9991999864578247,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9979000091552734,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9930999875068665,"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":0.8428341150283813},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6766509413719177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6496065855026245},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5670892596244812},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5278030633926392},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4774911105632782},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.45008745789527893},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3843180537223816}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8428341150283813},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6766509413719177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6496065855026245},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5670892596244812},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5278030633926392},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4774911105632782},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.45008745789527893},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3843180537223816}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2024.3369862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2024.3369862","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2979006455","display_name":null,"funder_award_id":"62276065","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3794798619","display_name":null,"funder_award_id":"U21A20472","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5846107237","display_name":null,"funder_award_id":"T00120210002","funder_id":"https://openalex.org/F4320331102","funder_display_name":"Shenzhen Research Institute of Big Data"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320331102","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1884731728","https://openalex.org/W2000117996","https://openalex.org/W2003244299","https://openalex.org/W2067191022","https://openalex.org/W2100495367","https://openalex.org/W2116516955","https://openalex.org/W2136922672","https://openalex.org/W2150102617","https://openalex.org/W2160616617","https://openalex.org/W2494395359","https://openalex.org/W2608862709","https://openalex.org/W2730106296","https://openalex.org/W2741943936","https://openalex.org/W2785678896","https://openalex.org/W2798534672","https://openalex.org/W2802061317","https://openalex.org/W2809829633","https://openalex.org/W2899604627","https://openalex.org/W2908035133","https://openalex.org/W2919087791","https://openalex.org/W2948398419","https://openalex.org/W2952171869","https://openalex.org/W2962852342","https://openalex.org/W2963250052","https://openalex.org/W2963462769","https://openalex.org/W2964118618","https://openalex.org/W2964732194","https://openalex.org/W2965940114","https://openalex.org/W2996832677","https://openalex.org/W2997223565","https://openalex.org/W2997707481","https://openalex.org/W2997770686","https://openalex.org/W3020986094","https://openalex.org/W3034363127","https://openalex.org/W3035524453","https://openalex.org/W3040730411","https://openalex.org/W3047570487","https://openalex.org/W3087208910","https://openalex.org/W3087801137","https://openalex.org/W3089039599","https://openalex.org/W3092253034","https://openalex.org/W3092707779","https://openalex.org/W3106709020","https://openalex.org/W3174519905","https://openalex.org/W3181871665","https://openalex.org/W3200696353","https://openalex.org/W3210298401","https://openalex.org/W4200583727","https://openalex.org/W4205660500","https://openalex.org/W4206213633","https://openalex.org/W4206471589","https://openalex.org/W4313156423","https://openalex.org/W6640963894","https://openalex.org/W6678914141","https://openalex.org/W6681875376","https://openalex.org/W6685380521","https://openalex.org/W6685777725","https://openalex.org/W6717434760","https://openalex.org/W6730333270","https://openalex.org/W6732395776","https://openalex.org/W6735913928","https://openalex.org/W6741832134","https://openalex.org/W6745535286","https://openalex.org/W6791237183","https://openalex.org/W6796756813"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W2967848559","https://openalex.org/W4299831724"],"abstract_inverted_index":{"Deep":[0],"learning-based":[1],"clustering":[2,70,86,149,173],"methods,":[3],"especially":[4],"those":[5],"incorporating":[6],"deep":[7,172],"generative":[8,22,91,126],"models,":[9],"have":[10],"recently":[11],"shown":[12],"noticeable":[13],"improvement":[14],"on":[15,183],"many":[16],"multimedia":[17,187],"benchmark":[18],"datasets.":[19],"However,":[20],"existing":[21],"models":[23,92,174],"still":[24],"suffer":[25],"from":[26,114,124],"unstable":[27],"training,":[28],"and":[29,66,77,103],"the":[30,36,56,98,101,108,115,131,147,152,157,160,194],"gradient":[31],"vanishes,":[32],"which":[33,88,122],"results":[34],"in":[35,61,130,151,163],"inability":[37],"to":[38,50,140,156],"learn":[39],"desirable":[40],"embedded":[41,64],"features":[42,65],"for":[43,72],"clustering.":[44,78,94],"In":[45],"this":[46,52,80],"paper,":[47],"we":[48,82,106,166],"aim":[49],"tackle":[51],"problem":[53,110],"by":[54,175],"exploring":[55],"capability":[57],"of":[58,111,159,171,196],"Wasserstein":[59,84,112,164],"embedding":[60,75,85,120,153],"learning":[62,76],"representative":[63],"introducing":[67],"a":[68,142],"new":[69],"module":[71,150],"jointly":[73],"optimizing":[74],"To":[79],"end,":[81],"propose":[83,168],"(WEC),":[87],"integrates":[89],"robust":[90],"with":[93,146,189],"By":[95],"directly":[96],"minimizing":[97],"discrepancy":[99],"between":[100],"prior":[102],"marginal":[104],"distribution,":[105],"transform":[107],"optimization":[109,144],"distance":[113],"original":[116,132],"data":[117,133],"space":[118],"into":[119],"space,":[121],"differs":[123],"other":[125],"approaches":[127],"that":[128],"optimize":[129],"space.":[134],"Consequently,":[135],"it":[136],"naturally":[137],"allows":[138],"us":[139],"construct":[141],"joint":[143],"framework":[145],"designed":[148],"layer.":[154],"Due":[155],"substitutability":[158],"penalty":[161,178],"term":[162],"embedding,":[165],"further":[167],"two":[169],"types":[170],"selecting":[176],"different":[177],"terms.":[179],"Comparative":[180],"experiments":[181],"conducted":[182],"nine":[184],"publicly":[185],"available":[186],"datasets":[188],"several":[190],"state-of-the-art":[191],"methods":[192],"demonstrate":[193],"effectiveness":[195],"our":[197],"method.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":28},{"year":2024,"cited_by_count":10}],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2025-10-10T00:00:00"}