{"id":"https://openalex.org/W4312201480","doi":"https://doi.org/10.3390/a16010014","title":"RMFRASL: Robust Matrix Factorization with Robust Adaptive Structure Learning for Feature Selection","display_name":"RMFRASL: Robust Matrix Factorization with Robust Adaptive Structure Learning for Feature Selection","publication_year":2022,"publication_date":"2022-12-26","ids":{"openalex":"https://openalex.org/W4312201480","doi":"https://doi.org/10.3390/a16010014"},"language":"en","primary_location":{"id":"doi:10.3390/a16010014","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16010014","pdf_url":"https://www.mdpi.com/1999-4893/16/1/14/pdf?version=1672052161","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/16/1/14/pdf?version=1672052161","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050851703","display_name":"Shumin Lai","orcid":"https://orcid.org/0000-0002-7338-7934"},"institutions":[{"id":"https://openalex.org/I53592917","display_name":"Jiangxi Normal University","ror":"https://ror.org/05nkgk822","country_code":"CN","type":"education","lineage":["https://openalex.org/I53592917"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shumin Lai","raw_affiliation_strings":["School of Software, Jiangxi Normal University, Nanchang 330022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Jiangxi Normal University, Nanchang 330022, China","institution_ids":["https://openalex.org/I53592917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056339977","display_name":"Longjun Huang","orcid":"https://orcid.org/0000-0001-6321-3378"},"institutions":[{"id":"https://openalex.org/I53592917","display_name":"Jiangxi Normal University","ror":"https://ror.org/05nkgk822","country_code":"CN","type":"education","lineage":["https://openalex.org/I53592917"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Longjun Huang","raw_affiliation_strings":["School of Software, Jiangxi Normal University, Nanchang 330022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Jiangxi Normal University, Nanchang 330022, China","institution_ids":["https://openalex.org/I53592917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100741315","display_name":"Ping Li","orcid":"https://orcid.org/0000-0002-8515-7773"},"institutions":[{"id":"https://openalex.org/I53592917","display_name":"Jiangxi Normal University","ror":"https://ror.org/05nkgk822","country_code":"CN","type":"education","lineage":["https://openalex.org/I53592917"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Li","raw_affiliation_strings":["School of Software, Jiangxi Normal University, Nanchang 330022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Jiangxi Normal University, Nanchang 330022, China","institution_ids":["https://openalex.org/I53592917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102017808","display_name":"Zhenzhen Luo","orcid":"https://orcid.org/0000-0002-1721-9151"},"institutions":[{"id":"https://openalex.org/I53592917","display_name":"Jiangxi Normal University","ror":"https://ror.org/05nkgk822","country_code":"CN","type":"education","lineage":["https://openalex.org/I53592917"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenzhen Luo","raw_affiliation_strings":["School of Software, Jiangxi Normal University, Nanchang 330022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Jiangxi Normal University, Nanchang 330022, China","institution_ids":["https://openalex.org/I53592917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100387975","display_name":"Jianzhong Wang","orcid":"https://orcid.org/0000-0002-6867-3282"},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzhong Wang","raw_affiliation_strings":["College of Information Science and Technology, Northeast Normal University, Changchun 130117, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Northeast Normal University, Changchun 130117, China","institution_ids":["https://openalex.org/I184983240"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074492862","display_name":"Yugen Yi","orcid":"https://orcid.org/0000-0001-9828-0319"},"institutions":[{"id":"https://openalex.org/I53592917","display_name":"Jiangxi Normal University","ror":"https://ror.org/05nkgk822","country_code":"CN","type":"education","lineage":["https://openalex.org/I53592917"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yugen Yi","raw_affiliation_strings":["School of Software, Jiangxi Normal University, Nanchang 330022, China"],"raw_orcid":"https://orcid.org/0000-0001-9828-0319","affiliations":[{"raw_affiliation_string":"School of Software, Jiangxi Normal University, Nanchang 330022, China","institution_ids":["https://openalex.org/I53592917"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056339977","https://openalex.org/A5074492862"],"corresponding_institution_ids":["https://openalex.org/I53592917"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":0.081,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.35133763,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"16","issue":"1","first_page":"14","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9911999702453613,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9837999939918518,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6441037654876709},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6318037509918213},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6222196817398071},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6134466528892517},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5740550756454468},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5610849261283875},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5252289772033691},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.48262056708335876},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4740599989891052},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.46169814467430115},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.45110100507736206},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40676116943359375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6441037654876709},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6318037509918213},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6222196817398071},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6134466528892517},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5740550756454468},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5610849261283875},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5252289772033691},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.48262056708335876},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4740599989891052},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.46169814467430115},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.45110100507736206},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40676116943359375},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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":3,"locations":[{"id":"doi:10.3390/a16010014","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16010014","pdf_url":"https://www.mdpi.com/1999-4893/16/1/14/pdf?version=1672052161","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9932abe89db14fc5bfd8fe4000c4f8f4","is_oa":false,"landing_page_url":"https://doaj.org/article/9932abe89db14fc5bfd8fe4000c4f8f4","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 16, Iss 1, p 14 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1999-4893/16/1/14/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/a16010014","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms; Volume 16; Issue 1; Pages: 14","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/a16010014","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16010014","pdf_url":"https://www.mdpi.com/1999-4893/16/1/14/pdf?version=1672052161","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2086286173","display_name":"\u57fa\u4e8e\u5f69\u8272\u773c\u5e95\u56fe\u50cf\u7684\u9752\u5149\u773c\u8f85\u52a9\u8bca\u65ad\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"62062040","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4594208545","display_name":null,"funder_award_id":"62006174","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6942826205","display_name":"\u8bfe\u5802\u73af\u5883\u4e0b\u57fa\u4e8e\u81ea\u7136\u611f\u77e5\u7684\u591a\u6a21\u6001\u5b66\u4e60\u5174\u8da3\u6c34\u5e73\u68c0\u6d4b\u7814\u7a76","funder_award_id":"61967010","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":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4312201480.pdf"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1902027874","https://openalex.org/W1976478782","https://openalex.org/W2002352636","https://openalex.org/W2015648984","https://openalex.org/W2052164429","https://openalex.org/W2076363162","https://openalex.org/W2083666679","https://openalex.org/W2084376194","https://openalex.org/W2103560185","https://openalex.org/W2108119513","https://openalex.org/W2123921160","https://openalex.org/W2149620660","https://openalex.org/W2579086357","https://openalex.org/W2587438737","https://openalex.org/W2609819335","https://openalex.org/W2623357190","https://openalex.org/W2747429511","https://openalex.org/W2753846453","https://openalex.org/W2763978449","https://openalex.org/W2795687440","https://openalex.org/W2807518743","https://openalex.org/W2809174326","https://openalex.org/W2894278606","https://openalex.org/W2898826688","https://openalex.org/W2906217954","https://openalex.org/W2933946304","https://openalex.org/W2998158283","https://openalex.org/W3000565840","https://openalex.org/W3080395176","https://openalex.org/W3109825681","https://openalex.org/W3118740333","https://openalex.org/W3120689699","https://openalex.org/W3126185976","https://openalex.org/W3132787779","https://openalex.org/W3161522379","https://openalex.org/W3165231040","https://openalex.org/W3197213531","https://openalex.org/W3197227262","https://openalex.org/W3206089627","https://openalex.org/W3211938211","https://openalex.org/W3217526930","https://openalex.org/W3217785399","https://openalex.org/W4285146107","https://openalex.org/W6669499580","https://openalex.org/W6676321539","https://openalex.org/W6681822384","https://openalex.org/W6682588271","https://openalex.org/W6804892872"],"related_works":["https://openalex.org/W2127243424","https://openalex.org/W2037504162","https://openalex.org/W4390394189","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2539013788","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W2075222291"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,27,56,61,88,98,125],"novel":[6],"unsupervised":[7,174],"feature":[8,65,95,150,175],"selection":[9,66,176],"method":[10,170],"termed":[11],"robust":[12,16,62,99],"matrix":[13,47,63,75],"factorization":[14],"with":[15,171],"adaptive":[17,49,100],"structure":[18,50,53,101,119,126,145],"learning":[19,102],"(RMFRASL),":[20],"which":[21,137],"can":[22],"select":[23],"discriminative":[24],"features":[25,141],"from":[26],"large":[28],"amount":[29],"of":[30,37,80,94,110,121,157,185],"multimedia":[31],"data":[32],"to":[33,76,90,115,142],"improve":[34],"the":[35,78,83,92,107,111,117,133,139,144,148,154,183,186],"performance":[36],"classification":[38],"and":[39,52,82],"clustering":[40],"tasks.":[41],"RMFRASL":[42,188],"integrates":[43],"three":[44],"models":[45],"(robust":[46],"factorization,":[48],"learning,":[51],"regularization)":[54],"into":[55],"unified":[57],"framework.":[58],"More":[59],"specifically,":[60],"factorization-based":[64],"(RMFFS)":[67],"model":[68,104],"is":[69,85,113,130,165,189],"proposed":[70,159,187],"by":[71],"introducing":[72],"an":[73,161],"indicator":[74],"measure":[77],"importance":[79],"features,":[81],"L21-norm":[84],"adopted":[86],"as":[87],"metric":[89],"enhance":[91],"robustness":[93],"selection.":[96],"Furthermore,":[97],"(RASL)":[103],"based":[105],"on":[106,132,178],"self-representation":[108],"capability":[109],"samples":[112],"designed":[114,131],"discover":[116],"geometric":[118],"relationships":[120],"original":[122],"data.":[123],"Lastly,":[124],"regularization":[127],"(SR)":[128],"term":[129],"learned":[134],"graph":[135],"structure,":[136],"constrains":[138],"selected":[140,149],"preserve":[143],"information":[146],"in":[147],"space.":[151],"To":[152],"solve":[153],"objective":[155],"function":[156],"our":[158,169],"RMFRASL,":[160],"iterative":[162],"optimization":[163],"algorithm":[164],"proposed.":[166],"By":[167],"comparing":[168],"some":[172],"state-of-the-art":[173],"approaches":[177],"several":[179],"publicly":[180],"available":[181],"databases,":[182],"advantage":[184],"demonstrated.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2023-01-04T00:00:00"}
