{"id":"https://openalex.org/W2096608935","doi":"https://doi.org/10.1109/tsp.2017.2649482","title":"High Dimensional Low Rank Plus Sparse Matrix Decomposition","display_name":"High Dimensional Low Rank Plus Sparse Matrix Decomposition","publication_year":2017,"publication_date":"2017-01-09","ids":{"openalex":"https://openalex.org/W2096608935","doi":"https://doi.org/10.1109/tsp.2017.2649482","mag":"2096608935"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2017.2649482","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2649482","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1502.00182","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101657195","display_name":"Mostafa Rahmani","orcid":"https://orcid.org/0000-0002-4140-383X"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mostafa Rahmani","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Fl., USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Fl., USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003612688","display_name":"George Atia","orcid":"https://orcid.org/0000-0001-7958-9855"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George K. Atia","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Fl., USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Fl., USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101657195"],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":11.1102,"has_fulltext":false,"cited_by_count":80,"citation_normalized_percentile":{"value":0.99263994,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"65","issue":"8","first_page":"2004","last_page":"2019"},"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":0.9961000084877014,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/row","display_name":"Row","score":0.591084897518158},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.552923321723938},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.517720639705658},{"id":"https://openalex.org/keywords/row-and-column-spaces","display_name":"Row and column spaces","score":0.5101357102394104},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.49487775564193726},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.48409759998321533},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4749324917793274},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47420862317085266},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4732545018196106},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.4701882600784302},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4688834846019745},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4375305771827698},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42477989196777344},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18159988522529602},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10012879967689514},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.0811968445777893}],"concepts":[{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.591084897518158},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.552923321723938},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.517720639705658},{"id":"https://openalex.org/C104140500","wikidata":"https://www.wikidata.org/wiki/Q2088159","display_name":"Row and column spaces","level":3,"score":0.5101357102394104},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.49487775564193726},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.48409759998321533},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4749324917793274},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47420862317085266},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4732545018196106},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.4701882600784302},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4688834846019745},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4375305771827698},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42477989196777344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18159988522529602},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10012879967689514},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0811968445777893},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tsp.2017.2649482","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2649482","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1502.00182","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1502.00182","pdf_url":"https://arxiv.org/pdf/1502.00182","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"},{"id":"pmh:oai:stars.library.ucf.edu:scopus2015-6465","is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/scopus2015/5466","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus Export 2015-2019","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1502.00182","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1502.00182","pdf_url":"https://arxiv.org/pdf/1502.00182","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":[],"awards":[{"id":"https://openalex.org/G6266848605","display_name":null,"funder_award_id":"CCF-1320547","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G659905212","display_name":null,"funder_award_id":"CCF-1552497","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":89,"referenced_works":["https://openalex.org/W198034206","https://openalex.org/W272277767","https://openalex.org/W1505090736","https://openalex.org/W1560153690","https://openalex.org/W1577111082","https://openalex.org/W1601029494","https://openalex.org/W1736339626","https://openalex.org/W1787402657","https://openalex.org/W1916337001","https://openalex.org/W1967336819","https://openalex.org/W1968691112","https://openalex.org/W1970833585","https://openalex.org/W1995168330","https://openalex.org/W1996287810","https://openalex.org/W1998058722","https://openalex.org/W1999352252","https://openalex.org/W2003753589","https://openalex.org/W2030449718","https://openalex.org/W2040387238","https://openalex.org/W2045390367","https://openalex.org/W2045983409","https://openalex.org/W2059283452","https://openalex.org/W2059355691","https://openalex.org/W2076410399","https://openalex.org/W2078465266","https://openalex.org/W2085927849","https://openalex.org/W2087445541","https://openalex.org/W2089135543","https://openalex.org/W2089784543","https://openalex.org/W2092239883","https://openalex.org/W2100556411","https://openalex.org/W2101117936","https://openalex.org/W2103012681","https://openalex.org/W2103972604","https://openalex.org/W2104989842","https://openalex.org/W2109357213","https://openalex.org/W2117173421","https://openalex.org/W2117377454","https://openalex.org/W2117756735","https://openalex.org/W2120961178","https://openalex.org/W2124252039","https://openalex.org/W2129131372","https://openalex.org/W2129638195","https://openalex.org/W2129812935","https://openalex.org/W2131172946","https://openalex.org/W2135525487","https://openalex.org/W2137103667","https://openalex.org/W2142077116","https://openalex.org/W2143701678","https://openalex.org/W2145096794","https://openalex.org/W2145962650","https://openalex.org/W2150489380","https://openalex.org/W2151793306","https://openalex.org/W2152356156","https://openalex.org/W2154304330","https://openalex.org/W2154992274","https://openalex.org/W2164452299","https://openalex.org/W2167167503","https://openalex.org/W2216683619","https://openalex.org/W2290340024","https://openalex.org/W2296319761","https://openalex.org/W2296616510","https://openalex.org/W2470359451","https://openalex.org/W2503308866","https://openalex.org/W2611328865","https://openalex.org/W2803670972","https://openalex.org/W2950958145","https://openalex.org/W2963166347","https://openalex.org/W2963363076","https://openalex.org/W2965497096","https://openalex.org/W3099514962","https://openalex.org/W3104624268","https://openalex.org/W4233413206","https://openalex.org/W4236177698","https://openalex.org/W4238472918","https://openalex.org/W4241684091","https://openalex.org/W4285719527","https://openalex.org/W4298184542","https://openalex.org/W6650267568","https://openalex.org/W6675479683","https://openalex.org/W6675879561","https://openalex.org/W6677334684","https://openalex.org/W6679168169","https://openalex.org/W6681016373","https://openalex.org/W6682218280","https://openalex.org/W6682766550","https://openalex.org/W6720261860","https://openalex.org/W6929283985","https://openalex.org/W6929385289"],"related_works":["https://openalex.org/W2313440505","https://openalex.org/W3123744736","https://openalex.org/W2137691148","https://openalex.org/W1505848319","https://openalex.org/W2905020035","https://openalex.org/W4281399881","https://openalex.org/W3166006430","https://openalex.org/W4281971614","https://openalex.org/W2049180840","https://openalex.org/W1992086467"],"abstract_inverted_index":{"This":[0],"paper":[1],"is":[2,63,95,99,122,131,136,142,199,208],"concerned":[3],"with":[4,38,42,174],"the":[5,22,27,43,46,87,114,125,137,143,146,158,171,183,191,194],"problem":[6,89,94,159],"of":[7,45,128,145,160,170,186,193],"lowrank":[8],"plus":[9],"sparse":[10,30],"matrix":[11,19],"decomposition":[12,20,88,98],"for":[13,18,66],"big":[14],"data.":[15,165,195],"Conventional":[16],"algorithms":[17,153],"use":[21],"entire":[23],"data":[24,70,106,115],"to":[25,90,156,190,201],"extract":[26],"low-rank":[28,147],"and":[29,32,140,177,204],"components,":[31],"are":[33,116,154],"based":[34],"on":[35,58],"optimization":[36],"problems":[37],"complexity":[39],"that":[40,72,85,124,179],"scales":[41],"dimension":[44],"data,":[47],"which":[48,62],"limits":[49],"their":[50],"scalability.":[51],"Furthermore,":[52],"existing":[53],"randomized":[54],"approaches":[55],"mostly":[56],"rely":[57],"uniform":[59],"random":[60],"sampling,":[61],"quite":[64],"inefficient":[65],"many":[67],"real":[68],"world":[69],"matrices":[71],"exhibit":[73],"additional":[74],"structures":[75],"(e.g.,":[76],"clustering).":[77],"In":[78,149],"this":[79],"paper,":[80],"a":[81,91,104],"scalable":[82],"subspace-pursuit":[83],"approach":[84,198],"transforms":[86],"subspace":[92],"learning":[93],"proposed.":[96,209],"The":[97,196],"carried":[100],"out":[101],"by":[102],"using":[103],"small":[105],"sketch":[107],"formed":[108],"from":[109,163],"sampled":[110,117,129,187],"columns/rows.":[111],"Even":[112],"when":[113],"uniformly":[118],"at":[119],"random,":[120],"it":[121],"shown":[123],"sufficient":[126],"number":[127,185],"columns/rows":[130,161,188],"roughly":[132],"O(r\u03bc),":[133],"where":[134],"\u03bc":[135],"coherency":[138],"parameter":[139],"r":[141],"rank":[144],"component.":[148],"addition,":[150],"adaptive":[151,175,180],"sampling":[152,162,176,181],"proposed":[155,172,197],"address":[157],"structured":[164],"We":[166],"provide":[167],"an":[168,205],"analysis":[169],"method":[173],"show":[178],"makes":[182],"required":[184],"invariant":[189],"distribution":[192],"amenable":[200],"online":[202,206],"implementation":[203],"scheme":[207]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":18},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}