{"id":"https://openalex.org/W3088453871","doi":"https://doi.org/10.1109/access.2020.3025096","title":"Adaptive Graph Regularized Low\u2013Rank Matrix Factorization With Noise and Outliers for Clustering","display_name":"Adaptive Graph Regularized Low\u2013Rank Matrix Factorization With Noise and Outliers for Clustering","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3088453871","doi":"https://doi.org/10.1109/access.2020.3025096","mag":"3088453871"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3025096","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3025096","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09201009.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09201009.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100769195","display_name":"Min Zhao","orcid":"https://orcid.org/0000-0001-7505-0721"},"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":"Min Zhao","raw_affiliation_strings":["School of Computer Science and Control Engineering, Yantai University, Yantai, China"],"raw_orcid":"https://orcid.org/0000-0001-7505-0721","affiliations":[{"raw_affiliation_string":"School of Computer Science and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024217969","display_name":"Jinglei Liu","orcid":"https://orcid.org/0000-0002-5388-6920"},"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":"Jinglei Liu","raw_affiliation_strings":["School of Computer Science and Control Engineering, Yantai University, Yantai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I18452120"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.1917,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.49393396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"8","issue":null,"first_page":"171851","last_page":"171863"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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":0.9994000196456909,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9979000091552734,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9958999752998352,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7708143591880798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6723329424858093},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5033361315727234},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4781854450702667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4559701979160309},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.387429803609848},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3638768792152405},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35163235664367676}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7708143591880798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6723329424858093},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5033361315727234},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4781854450702667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4559701979160309},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.387429803609848},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3638768792152405},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35163235664367676}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3025096","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3025096","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09201009.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ac8e3d40b83e4632bf263f0510df84cc","is_oa":true,"landing_page_url":"https://doaj.org/article/ac8e3d40b83e4632bf263f0510df84cc","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 171851-171863 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3025096","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3025096","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09201009.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G212376329","display_name":null,"funder_award_id":"61773331","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2436942900","display_name":null,"funder_award_id":"61703360","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"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"},{"id":"https://openalex.org/G5980039268","display_name":null,"funder_award_id":"61572419","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3088453871.pdf","grobid_xml":"https://content.openalex.org/works/W3088453871.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W132730096","https://openalex.org/W191001584","https://openalex.org/W1167991212","https://openalex.org/W1243961807","https://openalex.org/W1507780841","https://openalex.org/W1736339626","https://openalex.org/W1747478015","https://openalex.org/W1902027874","https://openalex.org/W1977556410","https://openalex.org/W1997201895","https://openalex.org/W2002469984","https://openalex.org/W2029069120","https://openalex.org/W2072275630","https://openalex.org/W2079558799","https://openalex.org/W2086023346","https://openalex.org/W2104290444","https://openalex.org/W2104819583","https://openalex.org/W2108119513","https://openalex.org/W2110531972","https://openalex.org/W2112104211","https://openalex.org/W2132914434","https://openalex.org/W2148694408","https://openalex.org/W2162316550","https://openalex.org/W2167686991","https://openalex.org/W2168103112","https://openalex.org/W2171837816","https://openalex.org/W2509903396","https://openalex.org/W2557275296","https://openalex.org/W2740503509","https://openalex.org/W2761260651","https://openalex.org/W2765771013","https://openalex.org/W2809034148","https://openalex.org/W2887891399","https://openalex.org/W2896059768","https://openalex.org/W2911895827","https://openalex.org/W2912958304","https://openalex.org/W2914720434","https://openalex.org/W2932864457","https://openalex.org/W2945634346","https://openalex.org/W2946643086","https://openalex.org/W2953072908","https://openalex.org/W2954752948","https://openalex.org/W2956105041","https://openalex.org/W2959148625","https://openalex.org/W2963316273","https://openalex.org/W2981580125","https://openalex.org/W2990387793","https://openalex.org/W2997701990","https://openalex.org/W2997770686","https://openalex.org/W4292023222","https://openalex.org/W6605304304","https://openalex.org/W6675747103","https://openalex.org/W6744423620","https://openalex.org/W6758841232","https://openalex.org/W6762833281","https://openalex.org/W6772338465","https://openalex.org/W6929385289"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2510582230","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W1977636359","https://openalex.org/W2772305933","https://openalex.org/W2580722822"],"abstract_inverted_index":{"Clustering,":[0],"which":[1,33,216],"is":[2,55,62,81,96,113,126,166,217],"a":[3,46,218],"commonly":[4],"used":[5],"tool,":[6],"has":[7,19,106],"been":[8],"applied":[9],"in":[10,30,39,169,212,222],"machine":[11],"learning,":[12],"data":[13,116],"mining":[14],"and":[15,18,28,75,104,118,161,187,214],"so":[16],"on,":[17],"received":[20],"extensive":[21],"research.":[22],"However,":[23],"there":[24],"are":[25],"usually":[26],"noise":[27,117],"outliers":[29],"the":[31,40,85,90,100,122,129,133,138,148,190],"data,":[32],"will":[34],"bring":[35],"about":[36],"significant":[37],"errors":[38],"clustering":[41,48,134,199,210],"results.":[42],"In":[43,88],"this":[44],"paper,":[45],"robust":[47],"model":[49],"with":[50],"adaptive":[51,123],"graph":[52,124],"regularization":[53,125],"(RCAG)":[54],"proposed,":[56],"on":[57,174],"which,":[58],"sparse":[59,66,86],"error":[60],"matrix":[61],"introduced":[63,82,127],"to":[64,83,115,131,153],"express":[65],"noise,":[67,71],"such":[68,181],"as":[69,182],"impulse":[70],"dead":[72],"line,":[73],"stripes,":[74],"\u2113":[76,91],"<sub":[77,92],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[78,93],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[79],"norm":[80,95],"alleviate":[84],"noise.":[87],"addition,":[89],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2,1</sub>":[94],"also":[97,167],"proposed":[98,193],"mitigating":[99],"effects":[101],"of":[102,164,177,192],"outliers,":[103],"it":[105],"rotation":[107],"invariance":[108],"property.":[109],"Therefore,":[110],"our":[111,206],"RCAG":[112,130,165],"insensitive":[114],"outliers.":[119],"More":[120],"importantly,":[121],"into":[128],"improve":[132],"performance.":[135],"Aiming":[136],"at":[137],"optimization":[139,156],"objective,":[140],"we":[141],"propose":[142],"an":[143],"iterative":[144],"updating":[145],"algorithm,":[146],"named":[147],"Augmented":[149],"Lagrangian":[150],"Method":[151],"(ALM),":[152],"update":[154],"each":[155],"variable":[157],"respectively.":[158],"The":[159,201],"convergence":[160],"time":[162],"complexity":[163],"proved":[168],"theory.":[170],"Finally,":[171],"experimental":[172,202],"results":[173,203],"fourteen":[175],"datasets":[176],"four":[178],"application":[179],"scenarios,":[180],"face":[183],"image,":[184],"handwriting":[185],"recognition":[186],"UCI,":[188],"elaborate":[189],"superiority":[191],"method":[194],"over":[195],"seven":[196],"existing":[197],"classical":[198],"methods.":[200],"demonstrate":[204],"that":[205],"approach":[207],"achieves":[208],"better":[209],"performance":[211],"ACC":[213],"Purity,":[215],"little":[219],"less":[220],"impressive":[221],"other":[223],"ways.":[224]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}