{"id":"https://openalex.org/W2925294014","doi":"https://doi.org/10.1109/tnnls.2019.2899073","title":"Weighted Mixed-Norm Regularized Regression for Robust Face Identification","display_name":"Weighted Mixed-Norm Regularized Regression for Robust Face Identification","publication_year":2019,"publication_date":"2019-03-20","ids":{"openalex":"https://openalex.org/W2925294014","doi":"https://doi.org/10.1109/tnnls.2019.2899073","mag":"2925294014","pmid":"https://pubmed.ncbi.nlm.nih.gov/30908239"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2019.2899073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2899073","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","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/A5026233608","display_name":"Jianwei Zheng","orcid":"https://orcid.org/0000-0001-6017-0552"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianwei Zheng","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6017-0552","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069529980","display_name":"Kechen Lou","orcid":null},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kechen Lou","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100613758","display_name":"Xi Yang","orcid":"https://orcid.org/0000-0003-2737-5948"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Yang","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2737-5948","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013768600","display_name":"Cong Bai","orcid":"https://orcid.org/0000-0002-6177-3862"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Bai","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6177-3862","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035112538","display_name":"Jinhui Tang","orcid":"https://orcid.org/0000-0001-9008-222X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhui Tang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-9008-222X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5026233608"],"corresponding_institution_ids":["https://openalex.org/I55712492"],"apc_list":null,"apc_paid":null,"fwci":2.5528,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.91783845,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"30","issue":"12","first_page":"3788","last_page":"3802"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9922000169754028,"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/T11448","display_name":"Face recognition and analysis","score":0.9916999936103821,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5587650537490845},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.5300202965736389},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5234634280204773},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4686194062232971},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4571599066257477},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4312629997730255},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4160730838775635},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3772861361503601},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35261401534080505},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.147853285074234},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.05929213762283325},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.052046388387680054}],"concepts":[{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5587650537490845},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.5300202965736389},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5234634280204773},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4686194062232971},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4571599066257477},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4312629997730255},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4160730838775635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3772861361503601},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35261401534080505},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.147853285074234},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.05929213762283325},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.052046388387680054},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2019.2899073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2899073","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:30908239","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30908239","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G2351125877","display_name":null,"funder_award_id":"61732007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3169447923","display_name":null,"funder_award_id":"LY18F020032","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G3254963032","display_name":null,"funder_award_id":"61772275","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3803982472","display_name":null,"funder_award_id":"61502424","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5526867466","display_name":null,"funder_award_id":"U1611461","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6051939103","display_name":null,"funder_award_id":"2016YFB1001001","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6212051606","display_name":null,"funder_award_id":"61602413","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7997273866","display_name":null,"funder_award_id":"LY19F030016","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W91744528","https://openalex.org/W317954863","https://openalex.org/W602182927","https://openalex.org/W756991363","https://openalex.org/W827142139","https://openalex.org/W1497088612","https://openalex.org/W1600550542","https://openalex.org/W1672851775","https://openalex.org/W1860736741","https://openalex.org/W1966443746","https://openalex.org/W1975815261","https://openalex.org/W1976503215","https://openalex.org/W1979920826","https://openalex.org/W1980500788","https://openalex.org/W2014697905","https://openalex.org/W2027325144","https://openalex.org/W2030158346","https://openalex.org/W2043661478","https://openalex.org/W2048023990","https://openalex.org/W2048695508","https://openalex.org/W2050849575","https://openalex.org/W2058009001","https://openalex.org/W2081930078","https://openalex.org/W2097486709","https://openalex.org/W2101149304","https://openalex.org/W2111854674","https://openalex.org/W2129812935","https://openalex.org/W2130187411","https://openalex.org/W2132467081","https://openalex.org/W2137823674","https://openalex.org/W2157069239","https://openalex.org/W2164278908","https://openalex.org/W2167577940","https://openalex.org/W2187214659","https://openalex.org/W2199944189","https://openalex.org/W2353169560","https://openalex.org/W2366739890","https://openalex.org/W2408458745","https://openalex.org/W2471758726","https://openalex.org/W2474352580","https://openalex.org/W2536626143","https://openalex.org/W2552639984","https://openalex.org/W2581851997","https://openalex.org/W2585551302","https://openalex.org/W2596264631","https://openalex.org/W2621864722","https://openalex.org/W2789432657","https://openalex.org/W2801765193","https://openalex.org/W3100203369","https://openalex.org/W3100830527","https://openalex.org/W3102415113","https://openalex.org/W3105835503","https://openalex.org/W3122534566","https://openalex.org/W4292363360","https://openalex.org/W6618411179","https://openalex.org/W6688016547"],"related_works":["https://openalex.org/W2384527366","https://openalex.org/W2285494230","https://openalex.org/W31220157","https://openalex.org/W1989621828","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W3083147128","https://openalex.org/W4236479416","https://openalex.org/W2165884543"],"abstract_inverted_index":{"Face":[0],"identification":[1,212],"(FI)":[2],"via":[3],"regression-based":[4,201],"classification":[5],"has":[6],"been":[7],"extensively":[8],"studied":[9],"during":[10],"the":[11,22,48,75,89,112,124,155,168,194,199,205,219,245,256],"recent":[12],"years.":[13],"Most":[14],"vector-based":[15,221],"methods":[16,30],"achieve":[17],"appealing":[18,209],"performance":[19,229,257],"in":[20,34,182,239],"handing":[21],"noncontiguous":[23,56],"pixelwise":[24],"noises,":[25],"while":[26],"some":[27],"matrix-based":[28,92,247],"regression":[29,69],"show":[31],"great":[32,162],"potential":[33],"dealing":[35],"with":[36,74,134,175,218,244],"contiguous":[37,54],"imagewise":[38],"noises.":[39],"However,":[40],"there":[41],"is":[42,152],"a":[43,66,115,139,143,183],"lack":[44],"of":[45,47,84,111,149,196,236],"consideration":[46],"mixture":[49,76],"noises":[50,57],"case,":[51],"where":[52],"both":[53,100],"and":[55,87,91,103,138,214,231],"are":[58,259],"jointly":[59],"contained.":[60],"In":[61],"this":[62],"paper,":[63],"we":[64],"propose":[65],"weighted":[67,118],"mixed-norm":[68],"(WMNR)":[70],"method":[71,148],"to":[72,263],"cope":[73],"image":[77,126],"corruption.":[78],"WMNR":[79,95,157,197,206],"reveals":[80],"certain":[81,173],"essential":[82],"characteristics":[83],"FI":[85],"problems":[86],"bridges":[88],"vector-":[90],"methods.":[93],"Particularly,":[94],"provides":[96],"two":[97],"advantages":[98,195],"for":[99,154],"theoretical":[101],"analysis":[102],"practical":[104],"implementation.":[105],"First,":[106],"it":[107,122,166,250],"generalizes":[108],"possible":[109],"distributions":[110],"residuals":[113],"into":[114,172],"unified":[116],"feature":[117],"loss":[119],"function.":[120],"Second,":[121],"constrains":[123],"residual":[125],"as":[127],"low-rank":[128],"structure":[129],"that":[130],"can":[131,179,266],"be":[132,180,267],"quantified":[133],"general":[135],"nonconvex":[136],"functions":[137],"weight":[140],"factor.":[141],"Moreover,":[142],"new":[144],"reweighted":[145],"alternating":[146],"direction":[147],"multipliers":[150],"algorithm":[151,160],"derived":[153],"proposed":[156],"model.":[158],"The":[159],"exhibits":[161],"computational":[163,215],"efficiency":[164],"since":[165],"divides":[167],"original":[169],"optimization":[170],"problem":[171],"subproblems":[174],"analytical":[176],"solution":[177],"or":[178],"implemented":[181],"parallel":[184],"manner.":[185],"Extensive":[186],"experiments":[187],"on":[188],"several":[189],"public":[190],"face":[191],"databases":[192],"demonstrate":[193],"over":[198],"state-of-the-art":[200],"approaches.":[202],"More":[203],"specifically,":[204],"achieves":[207,225],"an":[208],"tradeoff":[210],"between":[211],"accuracy":[213],"efficiency.":[216],"Compared":[217,243],"pure":[220,246],"methods,":[222,248],"our":[223],"approach":[224],"more":[226,233,253],"than":[227,234],"10%":[228],"improvement":[230,265],"saves":[232],"70%":[235],"runtime,":[237],"especially":[238],"severe":[240],"corruption":[241],"scenarios.":[242],"although":[249],"requires":[251],"slightly":[252],"computation":[254],"time,":[255],"benefits":[258],"even":[260],"larger;":[261],"up":[262],"20%":[264],"obtained.":[268]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
