{"id":"https://openalex.org/W4391696966","doi":"https://doi.org/10.1109/tnnls.2024.3357087","title":"Anchor-Sharing and Cluster-Wise Contrastive Network for Multiview Representation Learning","display_name":"Anchor-Sharing and Cluster-Wise Contrastive Network for Multiview Representation Learning","publication_year":2024,"publication_date":"2024-02-09","ids":{"openalex":"https://openalex.org/W4391696966","doi":"https://doi.org/10.1109/tnnls.2024.3357087","pmid":"https://pubmed.ncbi.nlm.nih.gov/38335084"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3357087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3357087","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/A5076122416","display_name":"Weiqing Yan","orcid":"https://orcid.org/0000-0001-7869-2404"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiqing Yan","raw_affiliation_strings":["School of Computer and Control Engineering, Yantai University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112985277","display_name":"Yuanyang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyang Zhang","raw_affiliation_strings":["School of Computer and Control Engineering, Yantai University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033240507","display_name":"Chang Tang","orcid":"https://orcid.org/0000-0002-6515-7696"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang Tang","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076872319","display_name":"Wujie Zhou","orcid":"https://orcid.org/0000-0002-3055-2493"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]},{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["CN","SG"],"is_corresponding":false,"raw_author_name":"Wujie Zhou","raw_affiliation_strings":["School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China","School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I168879160"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100403129","display_name":"Weisi Lin","orcid":"https://orcid.org/0000-0001-9866-1947"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Weisi Lin","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5076122416"],"corresponding_institution_ids":["https://openalex.org/I18452120"],"apc_list":null,"apc_paid":null,"fwci":10.6405,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.98962149,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"36","issue":"2","first_page":"3797","last_page":"3807"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.995199978351593,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.995199978351593,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9940999746322632,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9939000010490417,"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/discriminative-model","display_name":"Discriminative model","score":0.8369688987731934},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.7274395227432251},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.691290020942688},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6521635055541992},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.6485161185264587},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6250669360160828},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6110669374465942},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5074517130851746},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4933444559574127},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46684157848358154},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36937883496284485},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35373055934906006}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8369688987731934},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7274395227432251},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.691290020942688},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6521635055541992},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.6485161185264587},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6250669360160828},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6110669374465942},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5074517130851746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4933444559574127},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46684157848358154},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36937883496284485},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35373055934906006},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3357087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3357087","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:38335084","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38335084","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":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G4305083883","display_name":null,"funder_award_id":"61801414","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":75,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1907775068","https://openalex.org/W1965555842","https://openalex.org/W1979089718","https://openalex.org/W2033178790","https://openalex.org/W2100495367","https://openalex.org/W2145862222","https://openalex.org/W2154478709","https://openalex.org/W2155904486","https://openalex.org/W2187089797","https://openalex.org/W2532039214","https://openalex.org/W2740464254","https://openalex.org/W2750384547","https://openalex.org/W2786585376","https://openalex.org/W2797653144","https://openalex.org/W2966840649","https://openalex.org/W2997739739","https://openalex.org/W3010318487","https://openalex.org/W3012918605","https://openalex.org/W3035663159","https://openalex.org/W3044096495","https://openalex.org/W3089039599","https://openalex.org/W3099677434","https://openalex.org/W3108655343","https://openalex.org/W3120213044","https://openalex.org/W3132023044","https://openalex.org/W3140079845","https://openalex.org/W3149863265","https://openalex.org/W3165231040","https://openalex.org/W3169978599","https://openalex.org/W3173972271","https://openalex.org/W3176694003","https://openalex.org/W3212924718","https://openalex.org/W4200226646","https://openalex.org/W4206441147","https://openalex.org/W4206635403","https://openalex.org/W4210518188","https://openalex.org/W4212834658","https://openalex.org/W4225877894","https://openalex.org/W4225942313","https://openalex.org/W4280554973","https://openalex.org/W4283798877","https://openalex.org/W4287891019","https://openalex.org/W4289341676","https://openalex.org/W4289535947","https://openalex.org/W4303645634","https://openalex.org/W4304701247","https://openalex.org/W4306404896","https://openalex.org/W4309363988","https://openalex.org/W4310266386","https://openalex.org/W4312106962","https://openalex.org/W4312973985","https://openalex.org/W4315926876","https://openalex.org/W4319068889","https://openalex.org/W4319879007","https://openalex.org/W4320060414","https://openalex.org/W4321780073","https://openalex.org/W4376619374","https://openalex.org/W4382202985","https://openalex.org/W4382203265","https://openalex.org/W4385245566","https://openalex.org/W4385489739","https://openalex.org/W4385764280","https://openalex.org/W4386071520","https://openalex.org/W6631190155","https://openalex.org/W6682991666","https://openalex.org/W6685380521","https://openalex.org/W6743688258","https://openalex.org/W6766978945","https://openalex.org/W6769882874","https://openalex.org/W6796530276","https://openalex.org/W6803318553","https://openalex.org/W6838877340","https://openalex.org/W6845922095","https://openalex.org/W6846866826"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3119773509","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W3048601286","https://openalex.org/W2965925734"],"abstract_inverted_index":{"Multiview":[0],"clustering":[1,33,78],"(MVC)":[2],"has":[3],"gained":[4],"significant":[5],"attention":[6],"as":[7,27],"it":[8,98,216],"enables":[9],"the":[10,36,42,63,93,115,128,137,180,197,206,219,225,229,242,254,268,282],"partitioning":[11],"of":[12,130,139,228],"samples":[13],"into":[14,123,174,246],"their":[15],"respective":[16],"categories":[17],"through":[18],"unsupervised":[19],"learning.":[20,165],"However,":[21,89],"there":[22],"are":[23],"a":[24,149,262],"few":[25],"issues":[26],"follows:":[28],"1)":[29],"many":[30,107],"existing":[31],"deep":[32,76],"methods":[34,108],"use":[35,109],"same":[37],"latent":[38],"features":[39,57,70],"to":[40,54,67,84,100,113,136,217,250],"achieve":[41],"conflict":[43,181,269],"objectives,":[44],"namely,":[45],"reconstruction":[46,51,183],"and":[47,105,157,171,184,211,213],"view":[48],"consistency.":[49,185],"The":[50],"objective":[52,65],"aims":[53],"preserve":[55],"view-specific":[56,169],"for":[58,162],"each":[59],"individual":[60],"view,":[61],"while":[62],"view-consistency":[64],"strives":[66],"obtain":[68,85],"common":[69,230],"across":[71],"all":[72],"views;":[73],"2)":[74],"some":[75],"embedded":[77],"(DEC)":[79],"approaches":[80,91],"adopt":[81],"view-wise":[82],"fusion":[83],"consensus":[86,103],"feature":[87,191],"representation.":[88],"these":[90,145],"overlook":[92],"correlation":[94],"between":[95,182,209,256],"samples,":[96,204,212],"making":[97],"challenging":[99],"derive":[101],"discriminative":[102,226],"representations;":[104,117],"3)":[106],"contrastive":[110,273],"learning":[111,153,170,173],"(CL)":[112],"align":[114],"view's":[116],"however,":[118],"they":[119],"do":[120],"not":[121],"take":[122],"account":[124],"cluster":[125],"information":[126],"during":[127],"construction":[129],"sample":[131],"pairs,":[132],"which":[133,178,195,240],"can":[134],"lead":[135],"presence":[138],"false":[140],"negative":[141,259],"pairs.":[142],"To":[143],"address":[144],"issues,":[146],"we":[147,167,187,236],"propose":[148],"novel":[150],"multiview":[151,163],"representation":[152,164,231],"network,":[154],"called":[155],"anchor-sharing":[156,190],"clusterwise":[158],"CL":[159],"(CwCL)":[160],"network":[161,176],"Specifically,":[166],"separate":[168],"view-common":[172],"different":[175,201,233],"branches,":[177],"addresses":[179],"Second,":[186],"design":[188,237],"an":[189],"aggregation":[192],"(ASFA)":[193],"module,":[194,239],"learns":[196],"sharing":[198],"anchors":[199,210],"from":[200,232,258],"batch":[202],"data":[203],"establishes":[205],"bipartite":[207],"relationship":[208],"further":[214],"leverages":[215],"improve":[218],"samples'":[220],"representations.":[221],"This":[222],"module":[223],"enhances":[224],"power":[227],"samples.":[234],"Third,":[235],"CwCL":[238],"incorporates":[241],"learned":[243],"transition":[244,264],"probability":[245],"CL,":[247],"allowing":[248],"us":[249],"focus":[251],"on":[252],"minimizing":[253],"similarity":[255],"representations":[257],"pairs":[260],"with":[261],"low":[263],"probability.":[265],"It":[266],"alleviates":[267],"in":[270],"previous":[271],"sample-level":[272],"alignment.":[274],"Experimental":[275],"results":[276],"demonstrate":[277],"that":[278],"our":[279],"method":[280],"outperforms":[281],"state-of-the-art":[283],"performance.":[284]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":12}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
