{"id":"https://openalex.org/W3183406698","doi":"https://doi.org/10.1109/tip.2021.3096086","title":"Joint Learning of Latent Similarity and Local Embedding for Multi-View Clustering","display_name":"Joint Learning of Latent Similarity and Local Embedding for Multi-View Clustering","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3183406698","doi":"https://doi.org/10.1109/tip.2021.3096086","mag":"3183406698","pmid":"https://pubmed.ncbi.nlm.nih.gov/34310300"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2021.3096086","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3096086","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","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/A5101599930","display_name":"Aiping Huang","orcid":"https://orcid.org/0000-0002-6354-9039"},"institutions":[{"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":"Aiping Huang","raw_affiliation_strings":["Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6354-9039","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016217185","display_name":"Weiling Chen","orcid":"https://orcid.org/0000-0002-1400-1659"},"institutions":[{"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":"Weiling Chen","raw_affiliation_strings":["Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-1400-1659","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057108758","display_name":"Tiesong Zhao","orcid":"https://orcid.org/0000-0002-7497-8883"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"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":"Tiesong Zhao","raw_affiliation_strings":["Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou, China","Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-7497-8883","affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002277899","display_name":"Chang Wen Chen","orcid":"https://orcid.org/0000-0002-6720-234X"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]},{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["HK","US"],"is_corresponding":false,"raw_author_name":"Chang Wen Chen","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo, The State University of New York, Buffalo, NY, USA","Department of Computing, The Hong Kong Polytechnic University, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-6720-234X","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo, The State University of New York, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3554,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.90491292,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"30","issue":null,"first_page":"6772","last_page":"6784"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9966999888420105,"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/T10057","display_name":"Face and Expression Recognition","score":0.9966999888420105,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7625284194946289},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.6754004955291748},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6504828929901123},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6341285705566406},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.5655218362808228},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5273975729942322},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4670350253582001},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.4489358365535736},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4320718050003052},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.42962801456451416},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09357813000679016}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7625284194946289},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.6754004955291748},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6504828929901123},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6341285705566406},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.5655218362808228},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5273975729942322},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4670350253582001},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.4489358365535736},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4320718050003052},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.42962801456451416},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09357813000679016}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2021.3096086","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3096086","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:34310300","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34310300","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4099999964237213}],"awards":[{"id":"https://openalex.org/G162953625","display_name":null,"funder_award_id":"61901119","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3814934662","display_name":null,"funder_award_id":"62001116","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G396191943","display_name":null,"funder_award_id":"2019J01222","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G5849380280","display_name":null,"funder_award_id":"2020J01466","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W201974436","https://openalex.org/W297461772","https://openalex.org/W1979089718","https://openalex.org/W2036987424","https://openalex.org/W2070753207","https://openalex.org/W2101324110","https://openalex.org/W2108502868","https://openalex.org/W2114207967","https://openalex.org/W2119362355","https://openalex.org/W2154415691","https://openalex.org/W2187089797","https://openalex.org/W2584959193","https://openalex.org/W2587115404","https://openalex.org/W2605146283","https://openalex.org/W2611926148","https://openalex.org/W2740464254","https://openalex.org/W2741998188","https://openalex.org/W2742098698","https://openalex.org/W2752197020","https://openalex.org/W2758611985","https://openalex.org/W2779176574","https://openalex.org/W2791255512","https://openalex.org/W2810594911","https://openalex.org/W2881233020","https://openalex.org/W2891953767","https://openalex.org/W2896169497","https://openalex.org/W2898199757","https://openalex.org/W2898233200","https://openalex.org/W2900665190","https://openalex.org/W2900980272","https://openalex.org/W2940460948","https://openalex.org/W2943996654","https://openalex.org/W2944111873","https://openalex.org/W2944775756","https://openalex.org/W2945288617","https://openalex.org/W2949579163","https://openalex.org/W2964289004","https://openalex.org/W2965028812","https://openalex.org/W2965624713","https://openalex.org/W2972477132","https://openalex.org/W2978780922","https://openalex.org/W2981903848","https://openalex.org/W2983762999","https://openalex.org/W2987021044","https://openalex.org/W2988613494","https://openalex.org/W2997969890","https://openalex.org/W3047358409","https://openalex.org/W3083629845","https://openalex.org/W3099865281","https://openalex.org/W4235169531","https://openalex.org/W6608209381","https://openalex.org/W6610472804","https://openalex.org/W6675134712","https://openalex.org/W6682991666","https://openalex.org/W6736441558"],"related_works":["https://openalex.org/W2559422900","https://openalex.org/W2171610853","https://openalex.org/W3144143113","https://openalex.org/W1979094538","https://openalex.org/W2287240295","https://openalex.org/W4382052822","https://openalex.org/W2997891905","https://openalex.org/W2125464731","https://openalex.org/W3161541212","https://openalex.org/W2134448697"],"abstract_inverted_index":{"Spectral":[0],"clustering":[1,24,41,178,195],"has":[2],"been":[3],"an":[4,105],"attractive":[5],"topic":[6],"in":[7],"the":[8,15,30,33,67,86,93,116,121,135,148,156],"field":[9],"of":[10,18,32,79,96,125,152,165],"computer":[11],"vision":[12],"due":[13],"to":[14,54,70,91],"extensive":[16],"growth":[17],"applications,":[19],"such":[20],"as":[21,75,137],"image":[22],"segmentation,":[23],"and":[25,61,99,142,155,169],"representation.":[26],"In":[27,43],"this":[28,44],"problem,":[29],"construction":[31],"similarity":[34,59,68,80,117,167],"matrix":[35,60,69,168],"is":[36,73,89,109,173],"a":[37,48,57,62,76,138,166,170],"vital":[38],"element":[39],"affecting":[40],"performance.":[42],"paper,":[45],"we":[46,133],"propose":[47],"multi-view":[49,182],"joint":[50,139],"learning":[51],"(MVJL)":[52],"framework":[53],"achieve":[55],"both":[56],"reliable":[58],"latent":[63],"low-dimensional":[64,107,171],"embedding.":[65],"Specifically,":[66],"be":[71],"learned":[72],"represented":[74],"convex":[77],"hull":[78],"matrices":[81],"from":[82],"different":[83],"views,":[84],"where":[85],"nuclear":[87],"norm":[88],"imposed":[90],"capture":[92],"principal":[94],"information":[95],"multiple":[97],"views":[98],"improve":[100],"robustness":[101],"against":[102],"noise/outliers.":[103],"Moreover,":[104],"effective":[106],"representation":[108],"obtained":[110],"by":[111],"applying":[112],"local":[113,122],"embedding":[114],"on":[115,187],"matrix,":[118],"which":[119,163],"preserves":[120],"intrinsic":[123],"structure":[124],"data":[126],"through":[127],"dimensionality":[128],"reduction.":[129],"With":[130],"these":[131],"techniques,":[132],"formulate":[134],"MVJL":[136,192],"optimization":[140],"problem":[141],"derive":[143],"its":[144],"mathematical":[145],"solution":[146],"with":[147,176],"alternating":[149],"direction":[150],"method":[151],"multipliers":[153],"strategy":[154],"proximal":[157],"gradient":[158],"descent":[159],"method.":[160],"The":[161],"solution,":[162],"consists":[164],"representation,":[172],"ultimately":[174],"integrated":[175],"spectral":[177],"or":[179],"K-means":[180],"for":[181],"clustering.":[183],"Extensive":[184],"experimental":[185],"results":[186],"real-world":[188],"datasets":[189],"demonstrate":[190],"that":[191],"achieves":[193],"superior":[194],"performance":[196],"over":[197],"other":[198],"state-of-the-art":[199],"methods.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}