{"id":"https://openalex.org/W2327730590","doi":"https://doi.org/10.1109/spac.2014.6982680","title":"Multi-view embedding learning via robust joint nonnegative matrix factorization","display_name":"Multi-view embedding learning via robust joint nonnegative matrix factorization","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2327730590","doi":"https://doi.org/10.1109/spac.2014.6982680","mag":"2327730590"},"language":"en","primary_location":{"id":"doi:10.1109/spac.2014.6982680","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spac.2014.6982680","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","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/A5028245257","display_name":"Weihua Ou","orcid":"https://orcid.org/0000-0001-5241-7703"},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weihua Ou","raw_affiliation_strings":["School of Mathematics and Computer Science, Guizhou Normal University, Guiyang, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Computer Science, Guizhou Normal University, Guiyang, China","institution_ids":["https://openalex.org/I154893126"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016164542","display_name":"Kesheng Zhang","orcid":"https://orcid.org/0000-0003-3910-1581"},"institutions":[{"id":"https://openalex.org/I4210156872","display_name":"Guizhou Institute of Technology","ror":"https://ror.org/05x510r30","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210156872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kesheng Zhang","raw_affiliation_strings":["School of Information Engineering, Guizhou Institute of Technology, Guiyang, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Guizhou Institute of Technology, Guiyang, China","institution_ids":["https://openalex.org/I4210156872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057095711","display_name":"Xinge You","orcid":"https://orcid.org/0009-0006-1450-9504"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinge You","raw_affiliation_strings":["Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100759521","display_name":"Fei Long","orcid":"https://orcid.org/0009-0000-1553-2171"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Long","raw_affiliation_strings":["College of Information Engineering, Guizhou University, Guiyang, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5028245257"],"corresponding_institution_ids":["https://openalex.org/I154893126"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22593598,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"367","issue":null,"first_page":"169","last_page":"174"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10057","display_name":"Face and Expression Recognition","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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6970282196998596},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.666549801826477},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6320792436599731},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5840923190116882},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5797503590583801},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5426656603813171},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5191459059715271},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4005647897720337},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3983696699142456},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34678971767425537},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1009332537651062}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6970282196998596},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.666549801826477},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6320792436599731},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5840923190116882},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5797503590583801},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5426656603813171},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5191459059715271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4005647897720337},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3983696699142456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34678971767425537},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1009332537651062},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spac.2014.6982680","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spac.2014.6982680","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1967722387","https://openalex.org/W1968580628","https://openalex.org/W1986817851","https://openalex.org/W2013029404","https://openalex.org/W2080744942","https://openalex.org/W2101324110","https://openalex.org/W2105431676","https://openalex.org/W2109857912","https://openalex.org/W2134407776","https://openalex.org/W2135160607","https://openalex.org/W2136294701","https://openalex.org/W2137823674","https://openalex.org/W2140245639","https://openalex.org/W2142674578","https://openalex.org/W2154415691","https://openalex.org/W2157069239","https://openalex.org/W2158703881","https://openalex.org/W2296319761","https://openalex.org/W2405459681","https://openalex.org/W3100830527","https://openalex.org/W4250589301","https://openalex.org/W6646952826","https://openalex.org/W6675134712","https://openalex.org/W6682991666","https://openalex.org/W6683255826","https://openalex.org/W6822831480"],"related_works":["https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W34555840","https://openalex.org/W2146544734"],"abstract_inverted_index":{"Real":[0],"data":[1,28,41],"often":[2,75],"are":[3,64,88,133],"comprised":[4],"of":[5,166],"multiple":[6,39],"modalities":[7],"or":[8,60,84],"different":[9,50,140,143,154,167],"views,":[10,155],"which":[11,42,91,132],"provide":[12],"complementary":[13],"and":[14,30,181,194],"consensus":[15,159],"information":[16,22],"to":[17,99,124,135,147,162],"each":[18,56,130],"other.":[19],"Exploring":[20],"those":[21,100],"is":[23,34,58,74],"important":[24],"for":[25,38,129,142],"the":[26,44,93,120,126,136,149,164,170],"multi-view":[27,95,109],"clustering":[29],"classification.":[31],"Multiview":[32],"embedding":[33,96,110],"an":[35],"effective":[36],"method":[37],"view":[40,57,78],"uncovers":[43],"common":[45,150],"latent":[46],"structure":[47],"shared":[48,152],"by":[49,67,138,153],"views.":[51,168],"Previous":[52],"studies":[53],"assumed":[54],"that":[55,76],"clean,":[59],"at":[61],"least":[62],"there":[63],"not":[65],"contaminated":[66],"noises.":[68],"However,":[69],"in":[70,196],"real":[71],"tasks,":[72],"it":[73,176,183],"every":[77],"might":[79],"be":[80],"suffered":[81],"from":[82],"noises":[83,137],"even":[85],"some":[86],"views":[87],"partially":[89],"missing,":[90],"renders":[92],"traditional":[94],"algorithm":[97,111],"fail":[98],"cases.":[101],"In":[102,145],"this":[103],"paper,":[104],"we":[105,156,174],"propose":[106],"a":[107,158],"novel":[108],"via":[112,184],"robust":[113,134],"joint":[114],"nonnegative":[115],"matrix":[116,160],"factorization.":[117],"We":[118],"utilize":[119],"correntropy":[121],"induced":[122],"metric":[123],"measure":[125],"reconstruction":[127],"error":[128],"view,":[131],"assigning":[139],"weight":[141],"entries.":[144],"order":[146],"uncover":[148],"subspace":[151,161],"define":[157],"constrain":[163],"disagreement":[165],"For":[169],"non-convex":[171],"objective":[172],"function,":[173],"formulate":[175],"into":[177],"half":[178],"quadratic":[179],"minimization":[180],"solve":[182],"update":[185],"scheme":[186],"efficiently.":[187],"The":[188],"experiments":[189],"results":[190],"show":[191],"its":[192],"effectiveness":[193],"robustness":[195],"multiview":[197],"clustering.":[198]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}