{"id":"https://openalex.org/W1609068386","doi":"https://doi.org/10.1109/ijcnn.2015.7280422","title":"Robust semi-supervised nonnegative matrix factorization","display_name":"Robust semi-supervised nonnegative matrix factorization","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1609068386","doi":"https://doi.org/10.1109/ijcnn.2015.7280422","mag":"1609068386"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2015.7280422","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280422","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","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/A5115694897","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0001-7431-8925"},"institutions":[{"id":"https://openalex.org/I9300472","display_name":"Bournemouth University","ror":"https://ror.org/05wwcw481","country_code":"GB","type":"education","lineage":["https://openalex.org/I9300472"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Jing Wang","raw_affiliation_strings":["Faculty of Science and Technology, Bournemouth University, UK","[Faculty of Science and Technology Bournemouth University, UK]"],"affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, Bournemouth University, UK","institution_ids":["https://openalex.org/I9300472"]},{"raw_affiliation_string":"[Faculty of Science and Technology Bournemouth University, UK]","institution_ids":["https://openalex.org/I9300472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101634634","display_name":"Feng Tian","orcid":"https://orcid.org/0000-0002-0047-5263"},"institutions":[{"id":"https://openalex.org/I9300472","display_name":"Bournemouth University","ror":"https://ror.org/05wwcw481","country_code":"GB","type":"education","lineage":["https://openalex.org/I9300472"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Feng Tian","raw_affiliation_strings":["Faculty of Science and Technology, Bournemouth University, UK","[Faculty of Science and Technology Bournemouth University, UK]"],"affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, Bournemouth University, UK","institution_ids":["https://openalex.org/I9300472"]},{"raw_affiliation_string":"[Faculty of Science and Technology Bournemouth University, UK]","institution_ids":["https://openalex.org/I9300472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039254805","display_name":"Chang Hong Liu","orcid":"https://orcid.org/0000-0002-2426-4014"},"institutions":[{"id":"https://openalex.org/I9300472","display_name":"Bournemouth University","ror":"https://ror.org/05wwcw481","country_code":"GB","type":"education","lineage":["https://openalex.org/I9300472"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chang Hong Liu","raw_affiliation_strings":["Department of Psychology, Bournemouth University, UK"],"affiliations":[{"raw_affiliation_string":"Department of Psychology, Bournemouth University, UK","institution_ids":["https://openalex.org/I9300472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070747726","display_name":"Xiao Wang","orcid":"https://orcid.org/0000-0001-5180-877X"},"institutions":[{"id":"https://openalex.org/I132369690","display_name":"Tianjin University of Science and Technology","ror":"https://ror.org/018rbtf37","country_code":"CN","type":"education","lineage":["https://openalex.org/I132369690"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Wang","raw_affiliation_strings":["School of Computer Science and Technology, Tianjin University, China","School of Computer Science and Technology, Tianjin University China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Tianjin University, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Technology, Tianjin University China","institution_ids":["https://openalex.org/I132369690"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5115694897"],"corresponding_institution_ids":["https://openalex.org/I9300472"],"apc_list":null,"apc_paid":null,"fwci":0.3682,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.66513124,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"5","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.998199999332428,"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":0.998199999332428,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9797000288963318,"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":0.9532999992370605,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.7986733317375183},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.6350701451301575},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6056150197982788},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5872144103050232},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5744460821151733},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.45478805899620056},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.44477295875549316},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4265378415584564},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.41095849871635437},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.41057854890823364},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3770497441291809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37178415060043335},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36627113819122314},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3281984031200409},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1195010244846344}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.7986733317375183},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.6350701451301575},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6056150197982788},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5872144103050232},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5744460821151733},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.45478805899620056},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.44477295875549316},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4265378415584564},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.41095849871635437},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41057854890823364},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3770497441291809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37178415060043335},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36627113819122314},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3281984031200409},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1195010244846344},{"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2015.7280422","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280422","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:gala.gre.ac.uk:30506","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401244","display_name":"Greenwich Academic Literature Archive (University of Greenwich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I55060895","host_organization_name":"University of Greenwich","host_organization_lineage":["https://openalex.org/I55060895"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1634005169","https://openalex.org/W1902027874","https://openalex.org/W2002469984","https://openalex.org/W2004182014","https://openalex.org/W2013029404","https://openalex.org/W2022978200","https://openalex.org/W2053090063","https://openalex.org/W2061017849","https://openalex.org/W2062403535","https://openalex.org/W2065605562","https://openalex.org/W2067317289","https://openalex.org/W2091334405","https://openalex.org/W2104290444","https://openalex.org/W2104819583","https://openalex.org/W2108119513","https://openalex.org/W2113359929","https://openalex.org/W2117553576","https://openalex.org/W2118375674","https://openalex.org/W2118718620","https://openalex.org/W2135029798","https://openalex.org/W2136171036","https://openalex.org/W2139823104","https://openalex.org/W2154872931","https://openalex.org/W2167686991","https://openalex.org/W2168103112","https://openalex.org/W2169658215","https://openalex.org/W2482276862","https://openalex.org/W2799061466","https://openalex.org/W2799148064","https://openalex.org/W2997701990","https://openalex.org/W3143596294","https://openalex.org/W6666583032","https://openalex.org/W6675747103","https://openalex.org/W6677759377","https://openalex.org/W6680012447","https://openalex.org/W6680434193","https://openalex.org/W6721880745","https://openalex.org/W6793301333"],"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/W2146544734","https://openalex.org/W2075222291"],"abstract_inverted_index":{"Nonnegative":[0],"matrix":[1,74],"factorization":[2,75],"(NMF),":[3],"which":[4,38,78],"aims":[5],"at":[6],"finding":[7],"parts-based":[8],"representations":[9],"of":[10,20,43,49,63,111,142,159,171,182],"nonnegative":[11,73],"data,":[12],"has":[13],"been":[14],"widely":[15],"applied":[16],"to":[17,94,132,175],"a":[18,46,70],"range":[19],"applications":[21],"such":[22],"as":[23,90],"data":[24,32,50,98,112,166],"clustering,":[25],"pattern":[26],"recognition":[27],"and":[28,36,113,116,151,184],"computer":[29],"vision.":[30],"Real-world":[31],"are":[33],"often":[34],"sparse":[35],"noisy":[37],"may":[39,51],"reduce":[40],"the":[41,61,87,97,100,104,109,140,152,156,169],"accuracy":[42,183],"representations.":[44,64],"And":[45],"small":[47],"portion":[48],"have":[52,103,138],"prior":[53],"label":[54,88,102],"information,":[55],"which,":[56],"if":[57],"utilized,":[58],"can":[59],"improve":[60],"discriminability":[62],"In":[65],"this":[66,143],"paper,":[67],"we":[68],"propose":[69],"robust":[71],"semi-supervised":[72],"(RSSN-MF)":[76],"approach":[77],"takes":[79],"all":[80],"factors":[81],"above":[82],"into":[83],"consideration.":[84],"RSSNMF":[85,172],"incorporates":[86],"information":[89],"an":[91],"additional":[92],"constraint":[93],"guarantee":[95],"that":[96],"with":[99],"same":[101,105],"representation.":[106],"It":[107],"addresses":[108],"sparsity":[110],"accommodates":[114],"noises":[115],"outliers":[117],"consistently":[118],"via":[119],"L":[120],"<sub":[121],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[122],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2,1</sub>":[123],"-norm.":[124],"An":[125],"iterative":[126],"updating":[127],"optimization":[128,144,160],"scheme":[129,145],"is":[130],"derived":[131],"solve":[133],"RSSNMF's":[134],"objective":[135],"function.":[136],"We":[137],"proven":[139],"convergence":[141],"by":[146],"utilizing":[147],"auxiliary":[148],"function":[149],"method":[150],"correctness":[153],"based":[154],"on":[155,164],"Karush-Kohn-Tucker":[157],"condition":[158],"theory.":[161],"Experiments":[162],"carried":[163],"well-known":[165],"sets":[167],"demonstrate":[168],"effectiveness":[170],"in":[173,180],"comparison":[174],"other":[176],"existing":[177],"state-of-the-art":[178],"approaches":[179],"terms":[181],"normalized":[185],"mutual":[186],"information.":[187]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}