{"id":"https://openalex.org/W2790573495","doi":"https://doi.org/10.1109/spac.2017.8304243","title":"Robust principal component analysis via joint \u2113<inf>2,1</inf>-norms minimization","display_name":"Robust principal component analysis via joint \u2113<inf>2,1</inf>-norms minimization","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2790573495","doi":"https://doi.org/10.1109/spac.2017.8304243","mag":"2790573495"},"language":"en","primary_location":{"id":"doi:10.1109/spac.2017.8304243","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spac.2017.8304243","pdf_url":null,"source":{"id":"https://openalex.org/S4306498208","display_name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5081499128","display_name":"Shuangyan Yi","orcid":"https://orcid.org/0000-0003-4771-6105"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangyan Yi","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100740560","display_name":"Zhenyu He","orcid":"https://orcid.org/0000-0001-5212-5882"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu He","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058312907","display_name":"Weiguo Yang","orcid":"https://orcid.org/0000-0002-7609-5136"},"institutions":[{"id":"https://openalex.org/I4210093050","display_name":"Konka (China)","ror":"https://ror.org/00qa3c235","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210093050"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei-guo Yang","raw_affiliation_strings":["Shenzhen Konka Communication Technology Company, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Konka Communication Technology Company, China","institution_ids":["https://openalex.org/I4210093050"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3184,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70115709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"17","issue":null,"first_page":"13","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9980999827384949,"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":0.9980999827384949,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9979000091552734,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9968000054359436,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.8316147327423096},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6373528838157654},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6097267866134644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.580007791519165},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.561592161655426},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5464634895324707},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4519686996936798},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.429697185754776}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.8316147327423096},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6373528838157654},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6097267866134644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.580007791519165},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.561592161655426},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5464634895324707},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4519686996936798},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.429697185754776},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/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.2017.8304243","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spac.2017.8304243","pdf_url":null,"source":{"id":"https://openalex.org/S4306498208","display_name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W147992333","https://openalex.org/W187956566","https://openalex.org/W191001584","https://openalex.org/W1513013675","https://openalex.org/W1682001760","https://openalex.org/W1736339626","https://openalex.org/W1975900269","https://openalex.org/W1992633833","https://openalex.org/W2007339694","https://openalex.org/W2009501510","https://openalex.org/W2053090063","https://openalex.org/W2055254373","https://openalex.org/W2060758047","https://openalex.org/W2063379935","https://openalex.org/W2076363162","https://openalex.org/W2081072950","https://openalex.org/W2089894294","https://openalex.org/W2098693229","https://openalex.org/W2129442239","https://openalex.org/W2140151376","https://openalex.org/W2145962650","https://openalex.org/W2155145150","https://openalex.org/W2155759509","https://openalex.org/W2171837816","https://openalex.org/W2182396527","https://openalex.org/W2298605637","https://openalex.org/W2398147772","https://openalex.org/W2400262625","https://openalex.org/W2402197802","https://openalex.org/W2507470109","https://openalex.org/W2522601641","https://openalex.org/W2725281289","https://openalex.org/W2737362155","https://openalex.org/W2963630677","https://openalex.org/W6603183647","https://openalex.org/W6607652939","https://openalex.org/W6607783561","https://openalex.org/W6712754916"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2364594919","https://openalex.org/W2126145365","https://openalex.org/W2167092671","https://openalex.org/W1995723671","https://openalex.org/W2164647769"],"abstract_inverted_index":{"Principal":[0,55],"Component":[1,56],"Analysis":[2,57],"(PCA)":[3],"is":[4,28,85,198],"the":[5,44,82,95,120,123,138,142,149,158,168,202,211,214],"most":[6],"widely":[7],"used":[8],"unsupervised":[9],"subspace":[10],"learning":[11],"method,":[12],"and":[13,74,122,129],"lots":[14],"of":[15,70,213],"its":[16,185],"variants":[17],"have":[18],"been":[19],"developed.":[20],"With":[21],"so":[22],"many":[23],"proposed":[24,83,199,215],"PCA-like":[25,80],"methods,":[26,81],"it":[27],"still":[29],"not":[30],"clear":[31],"that":[32,113],"which":[33,62],"features":[34,90,112,160],"are":[35],"better":[36],"or":[37],"worse":[38],"for":[39,91],"principal":[40],"components,":[41],"especially":[42],"when":[43],"data":[45,140,144],"suffers":[46],"from":[47,141],"outliers.":[48,77,191],"To":[49],"this":[50,147],"end,":[51],"we":[52,101,171],"propose":[53],"Robust":[54],"via":[58],"joint":[59],"\u21132,1-norms":[60],"minimization,":[61],"provides":[63],"new":[64],"insights":[65],"into":[66],"two":[67],"crucial":[68],"issues":[69],"PCA:":[71],"feature":[72],"selection":[73],"robustness":[75],"to":[76,87,109,136,179,183,200],"Unlike":[78],"other":[79,169],"method":[84],"able":[86],"select":[88,110,180],"effective":[89,111,159,195],"reconstruction":[92],"by":[93,156,162],"using":[94,157],"\u21132,1-norm":[96,105,174],"regularization":[97],"term.":[98],"More":[99],"specific,":[100],"first":[102],"use":[103,131],"a":[104,126,163,176],"based":[106],"transformation":[107,134,165],"matrix":[108,135],"can":[114,152],"effectively":[115],"characterize":[116],"key":[117,150],"components":[118,151],"(e.g.,":[119],"eyes":[121],"nose":[124],"in":[125],"face":[127],"image),":[128],"then":[130],"an":[132],"orthogonal":[133],"recover":[137,184],"original":[139],"selected":[143,161],"representation.":[145],"In":[146],"way,":[148],"be":[153],"well":[154],"recovered":[155],"learned":[164],"matrix.":[166],"On":[167],"hand,":[170],"also":[172],"impose":[173],"on":[175,207],"loss":[177],"term":[178],"clean":[181],"samples":[182,188],"same":[186],"class":[187],"but":[189],"with":[190],"A":[192],"simple":[193],"yet":[194],"optimization":[196,204],"algorithm":[197],"solve":[201],"resulting":[203],"problem.":[205],"Experiments":[206],"six":[208],"datasets":[209],"demonstrate":[210],"effectiveness":[212],"method.":[216]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}