{"id":"https://openalex.org/W2925293321","doi":"https://doi.org/10.1137/17m1178346","title":"Fast Multilevel Algorithms for Compressive Principal Component Pursuit","display_name":"Fast Multilevel Algorithms for Compressive Principal Component Pursuit","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2925293321","doi":"https://doi.org/10.1137/17m1178346","mag":"2925293321"},"language":"en","primary_location":{"id":"doi:10.1137/17m1178346","is_oa":false,"landing_page_url":"https://doi.org/10.1137/17m1178346","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2206.13369","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110629211","display_name":"Vahan Hovhannisyan","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Vahan Hovhannisyan","raw_affiliation_strings":["Department of Computing, Imperial College London, 180 Queen's Gate, SW7 2AZ London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College London, 180 Queen's Gate, SW7 2AZ London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050734738","display_name":"Yannis Panagakis","orcid":"https://orcid.org/0000-0003-0153-5210"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yannis Panagakis","raw_affiliation_strings":["Department of Computing, Imperial College London, 180 Queen's Gate, SW7 2AZ London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College London, 180 Queen's Gate, SW7 2AZ London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083174192","display_name":"Panos Parpas","orcid":"https://orcid.org/0000-0002-2817-2301"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Panos Parpas","raw_affiliation_strings":["Department of Computing, Imperial College London, 180 Queen's Gate, SW7 2AZ London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College London, 180 Queen's Gate, SW7 2AZ London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080553022","display_name":"Stefanos Zafeiriou","orcid":"https://orcid.org/0000-0002-5222-1740"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Stefanos Zafeiriou","raw_affiliation_strings":["Department of Computing, Imperial College London, 180 Queen's Gate, SW7 2AZ London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College London, 180 Queen's Gate, SW7 2AZ London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5110629211"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.3868,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.5775901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"12","issue":"1","first_page":"624","last_page":"649"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9972000122070312,"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":0.7590557336807251},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6410880088806152},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.573383092880249},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.5626829862594604},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4877341687679291},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48425671458244324},{"id":"https://openalex.org/keywords/basis-pursuit","display_name":"Basis pursuit","score":0.4801144599914551},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.4471589922904968},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.43127143383026123},{"id":"https://openalex.org/keywords/sparse-pca","display_name":"Sparse PCA","score":0.42016690969467163},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.374492883682251},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34873807430267334},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13128533959388733}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7590557336807251},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6410880088806152},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.573383092880249},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.5626829862594604},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4877341687679291},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48425671458244324},{"id":"https://openalex.org/C99217422","wikidata":"https://www.wikidata.org/wiki/Q4867576","display_name":"Basis pursuit","level":4,"score":0.4801144599914551},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.4471589922904968},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.43127143383026123},{"id":"https://openalex.org/C24252448","wikidata":"https://www.wikidata.org/wiki/Q7573786","display_name":"Sparse PCA","level":3,"score":0.42016690969467163},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.374492883682251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34873807430267334},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13128533959388733},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1137/17m1178346","is_oa":false,"landing_page_url":"https://doi.org/10.1137/17m1178346","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2206.13369","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.13369","pdf_url":"https://arxiv.org/pdf/2206.13369","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:spiral.imperial.ac.uk:10044/1/66138","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/66138","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"649","raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2206.13369","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.13369","pdf_url":"https://arxiv.org/pdf/2206.13369","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8299999833106995}],"awards":[{"id":"https://openalex.org/G3612313539","display_name":null,"funder_award_id":"EP/M028240/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G5547861214","display_name":null,"funder_award_id":"EP/K040723/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1517295252","https://openalex.org/W1530872699","https://openalex.org/W1760407951","https://openalex.org/W1874745161","https://openalex.org/W1950149046","https://openalex.org/W1970576574","https://openalex.org/W1974042113","https://openalex.org/W1976792725","https://openalex.org/W2013243898","https://openalex.org/W2013854956","https://openalex.org/W2022394524","https://openalex.org/W2028781966","https://openalex.org/W2045261328","https://openalex.org/W2067251371","https://openalex.org/W2071128523","https://openalex.org/W2079558799","https://openalex.org/W2094394132","https://openalex.org/W2111861511","https://openalex.org/W2115706991","https://openalex.org/W2123921160","https://openalex.org/W2124252039","https://openalex.org/W2136885855","https://openalex.org/W2145962650","https://openalex.org/W2177697562","https://openalex.org/W2462506789","https://openalex.org/W2482870886","https://openalex.org/W2559655401","https://openalex.org/W2765339558","https://openalex.org/W2781517632","https://openalex.org/W2906621894","https://openalex.org/W2912522929","https://openalex.org/W2913535645","https://openalex.org/W2962966677","https://openalex.org/W2963706461","https://openalex.org/W3105677939","https://openalex.org/W3111652977","https://openalex.org/W3188779072","https://openalex.org/W4236965008","https://openalex.org/W4238805501","https://openalex.org/W4297776040"],"related_works":["https://openalex.org/W2108275041","https://openalex.org/W2949587108","https://openalex.org/W2249469762","https://openalex.org/W2294690908","https://openalex.org/W2011611369","https://openalex.org/W1992008660","https://openalex.org/W2116148865","https://openalex.org/W2160547390","https://openalex.org/W59030693","https://openalex.org/W1998873033"],"abstract_inverted_index":{"Recovering":[0],"a":[1,34,55,59,75,142,197],"low-rank":[2,35,56,84,191],"matrix":[3,36,51,57,80,85],"from":[4,37],"highly":[5],"corrupted":[6],"measurements":[7],"arises":[8],"in":[9,131,163,196],"compressed":[10],"sensing":[11],"of":[12,42,77,134,148,165],"structured":[13],"high-dimensional":[14],"signals":[15],"(e.g.,":[16],"videos":[17],"and":[18,45,58,66,99,105,150,172,211,228,247],"hyperspectral":[19],"images":[20],"among":[21],"others).":[22],"Robust":[23],"principal":[24,29,93],"component":[25,30,94,192],"analysis,":[26],"solved":[27],"via":[28],"pursuit":[31,95],"(PCP),":[32],"recovers":[33],"sparse":[38,60,64],"corruptions":[39],"that":[40,189,203,232],"are":[41,101,207,237],"unknown":[43],"value":[44,120],"support":[46],"by":[47,89],"decomposing":[48],"the":[49,69,78,91,132,146,169,178,187,190,204,214,233],"observation":[50],"into":[52],"two":[53],"terms,":[54],"one,":[61],"accounting":[62],"for":[63,112,145],"noise":[65],"outliers.":[67],"In":[68,137],"more":[70],"general":[71],"setting,":[72],"where":[73],"only":[74],"fraction":[76],"data":[79],"has":[81],"been":[82,110],"observed,":[83],"recovery":[86],"is":[87,159],"achieved":[88],"solving":[90],"compressive":[92],"(CPCP).":[96],"Both":[97],"PCP":[98,149,246],"CPCP":[100,151],"well-studied":[102],"convex":[103],"programs,":[104],"numerous":[106,226],"iterative":[107],"algorithms":[108,117,206,236],"have":[109],"proposed":[111,205,234],"their":[113,128,242],"optimization.":[114],"Nevertheless,":[115],"these":[116],"involve":[118],"singular":[119],"decomposition":[121],"(SVD)":[122],"at":[123,213],"each":[124],"iteration,":[125],"which":[126],"renders":[127],"applicability":[129],"challenging":[130],"case":[133],"massive":[135],"data.":[136],"this":[138],"paper,":[139],"we":[140],"propose":[141],"multilevel":[143,235],"approach":[144],"solution":[147,176],"problems.":[152],"The":[153],"core":[154],"principle":[155],"behind":[156],"our":[157,183],"algorithm":[158],"to":[160,177,209],"apply":[161],"SVD":[162],"models":[164],"lower":[166,198,220],"dimensionality":[167],"than":[168,241],"original":[170,179,243],"one":[171],"then":[173],"lift":[174],"its":[175],"problem":[180],"dimension.":[181],"Hence,":[182],"methods":[184],"rely":[185],"on":[186,225],"assumption":[188],"can":[193],"be":[194],"represented":[195],"dimensional":[199],"space.":[200],"We":[201],"show":[202],"easy":[208],"implement":[210],"converge":[212],"same":[215],"rate":[216],"but":[217],"with":[218],"much":[219],"iteration":[221],"cost.":[222],"Numerical":[223],"experiments":[224],"synthetic":[227],"real":[229],"problems":[230],"indicate":[231],"several":[238],"times":[239],"faster":[240],"counterparts,":[244],"namely,":[245],"CPCP.":[248]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-04-01T00:00:00"}