{"id":"https://openalex.org/W3093365368","doi":"https://doi.org/10.1109/lsp.2020.3044130","title":"Rapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank Estimation","display_name":"Rapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank Estimation","publication_year":2020,"publication_date":"2020-12-11","ids":{"openalex":"https://openalex.org/W3093365368","doi":"https://doi.org/10.1109/lsp.2020.3044130","mag":"3093365368"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.3044130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3044130","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2010.07422","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103070466","display_name":"HanQin Cai","orcid":"https://orcid.org/0000-0002-2937-1986"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"HanQin Cai","raw_affiliation_strings":["Department of Mathematics, University of California, Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064380948","display_name":"Keaton Hamm","orcid":"https://orcid.org/0000-0003-0719-6045"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keaton Hamm","raw_affiliation_strings":["Department of Mathematics, University of Texas at Arlington, Arlington, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Texas at Arlington, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035286718","display_name":"Longxiu Huang","orcid":"https://orcid.org/0000-0002-6610-9653"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Longxiu Huang","raw_affiliation_strings":["Department of Mathematics, University of California, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-6610-9653","affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100325973","display_name":"Jiaqi Li","orcid":"https://orcid.org/0000-0003-3743-9351"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Li","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100453475","display_name":"Tao Wang","orcid":"https://orcid.org/0000-0002-1391-7331"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Wang","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103070466"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":5.5714,"has_fulltext":false,"cited_by_count":61,"citation_normalized_percentile":{"value":0.9741818,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"28","issue":null,"first_page":"116","last_page":"120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9991000294685364,"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/T10057","display_name":"Face and Expression Recognition","score":0.9976000189781189,"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/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.9154999256134033},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.7124297618865967},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6257566213607788},{"id":"https://openalex.org/keywords/block-matrix","display_name":"Block matrix","score":0.5763517618179321},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.572542130947113},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5591999888420105},{"id":"https://openalex.org/keywords/iterated-function","display_name":"Iterated function","score":0.5375490188598633},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5227832198143005},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.4899543821811676},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.48413094878196716},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.475900262594223},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4566049873828888},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.42353302240371704},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4235290586948395},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4227648079395294},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4152839183807373},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4145349860191345},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2759723365306854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18115556240081787}],"concepts":[{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.9154999256134033},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7124297618865967},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6257566213607788},{"id":"https://openalex.org/C85817219","wikidata":"https://www.wikidata.org/wiki/Q884772","display_name":"Block matrix","level":3,"score":0.5763517618179321},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.572542130947113},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5591999888420105},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.5375490188598633},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5227832198143005},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.4899543821811676},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.48413094878196716},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.475900262594223},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4566049873828888},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.42353302240371704},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4235290586948395},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4227648079395294},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4152839183807373},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4145349860191345},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2759723365306854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18115556240081787},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"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/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/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2020.3044130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3044130","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2010.07422","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.07422","pdf_url":"https://arxiv.org/pdf/2010.07422","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2010.07422","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.07422","pdf_url":"https://arxiv.org/pdf/2010.07422","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.4000000059604645,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G4693844897","display_name":null,"funder_award_id":"N0001417121","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G6710005501","display_name":null,"funder_award_id":"CCF-1740858","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"}],"funders":[{"id":"https://openalex.org/F4320335353","display_name":"National Science Foundation of Sri Lanka","ror":"https://ror.org/010xaa060"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1974042113","https://openalex.org/W1995168330","https://openalex.org/W2001178002","https://openalex.org/W2003753589","https://openalex.org/W2075103606","https://openalex.org/W2106037979","https://openalex.org/W2111040408","https://openalex.org/W2120580172","https://openalex.org/W2129812935","https://openalex.org/W2134327945","https://openalex.org/W2141696759","https://openalex.org/W2145962650","https://openalex.org/W2403076655","https://openalex.org/W2461893856","https://openalex.org/W2462481369","https://openalex.org/W2723797911","https://openalex.org/W2742757407","https://openalex.org/W2807024067","https://openalex.org/W2892000577","https://openalex.org/W2950082039","https://openalex.org/W2962714108","https://openalex.org/W2962872245","https://openalex.org/W2963295147","https://openalex.org/W2963798309","https://openalex.org/W2964138364","https://openalex.org/W2964321615","https://openalex.org/W2969530042","https://openalex.org/W2971963065","https://openalex.org/W2976673205","https://openalex.org/W2979756219","https://openalex.org/W3024000234","https://openalex.org/W3025612414","https://openalex.org/W3043060394","https://openalex.org/W3104624268","https://openalex.org/W3114287677","https://openalex.org/W3134139903","https://openalex.org/W3192692954","https://openalex.org/W6675840925","https://openalex.org/W6676847830","https://openalex.org/W6679984830","https://openalex.org/W6713161955","https://openalex.org/W6740285172","https://openalex.org/W6745893055","https://openalex.org/W6767155348","https://openalex.org/W6768554705","https://openalex.org/W6777674752"],"related_works":["https://openalex.org/W2890107589","https://openalex.org/W2802788970","https://openalex.org/W2125326641","https://openalex.org/W3208119034","https://openalex.org/W2001342884","https://openalex.org/W4390143385","https://openalex.org/W3196545307","https://openalex.org/W3089517991","https://openalex.org/W2973685100","https://openalex.org/W2507476065"],"abstract_inverted_index":{"Robust":[0,24],"principal":[1],"component":[2],"analysis":[3],"(RPCA)":[4],"is":[5,74],"a":[6,18],"widely":[7],"used":[8],"tool":[9],"for":[10,27],"dimension":[11],"reduction.":[12],"In":[13],"this":[14,45],"work,":[15],"we":[16],"propose":[17],"novel":[19],"non-convex":[20],"algorithm,":[21],"coined":[22],"Iterated":[23],"CUR":[25,49],"(IRCUR),":[26],"solving":[28],"RPCA":[29],"problems,":[30],"which":[31,57],"dramatically":[32],"improves":[33],"the":[34,40,53,79,84,91,97,103],"computational":[35,98],"efficiency":[36],"in":[37],"comparison":[38],"with":[39],"existing":[41],"algorithms.":[42],"IRCUR":[43,73,101],"achieves":[44],"acceleration":[46],"by":[47],"employing":[48],"decomposition":[50],"when":[51],"updating":[52],"low":[54,64],"rank":[55,65],"component,":[56],"allows":[58],"us":[59],"to":[60,76],"obtain":[61],"an":[62],"accurate":[63],"approximation":[66],"via":[67],"only":[68,78],"three":[69],"small":[70,80],"submatrices.":[71],"Consequently,":[72],"able":[75],"process":[77],"submatrices":[81],"and":[82,109],"avoid":[83],"expensive":[85],"computing":[86],"on":[87,106],"full":[88],"matrix":[89],"through":[90],"entire":[92],"algorithm.":[93],"Numerical":[94],"experiments":[95],"establish":[96],"advantage":[99],"of":[100],"over":[102],"state-of-art":[104],"algorithms":[105],"both":[107],"synthetic":[108],"real-world":[110],"datasets.":[111]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":12}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
