{"id":"https://openalex.org/W7126064444","doi":"https://doi.org/10.1109/tpami.2026.3659200","title":"Robust Matrix Completion With Deterministic Sampling via Convex Optimization","display_name":"Robust Matrix Completion With Deterministic Sampling via Convex Optimization","publication_year":2026,"publication_date":"2026-01-29","ids":{"openalex":"https://openalex.org/W7126064444","doi":"https://doi.org/10.1109/tpami.2026.3659200","pmid":"https://pubmed.ncbi.nlm.nih.gov/41610361"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2026.3659200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3659200","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","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/A5018553723","display_name":"Yinjian Wang","orcid":"https://orcid.org/0009-0005-9499-6826"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinjian Wang","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-9499-6826","affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124288396","display_name":"Wei Li","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7015-7335","affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078795882","display_name":"James E. Fowler","orcid":"https://orcid.org/0000-0003-2005-405X"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James E. Fowler","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA"],"raw_orcid":"https://orcid.org/0000-0003-2005-405X","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124216424","display_name":"Gemine Vivone","orcid":null},"institutions":[{"id":"https://openalex.org/I4210115556","display_name":"National Research Council - Institute of Methodologies for Environmental Analysis","ror":"https://ror.org/024ye7w89","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210115556","https://openalex.org/I4210155236"]},{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Gemine Vivone","raw_affiliation_strings":["National Research Council, Institute of Methodologies for Environmental Analysis (CNR-IMAA), Tito, Italy"],"raw_orcid":"https://orcid.org/0000-0001-9542-0638","affiliations":[{"raw_affiliation_string":"National Research Council, Institute of Methodologies for Environmental Analysis (CNR-IMAA), Tito, Italy","institution_ids":["https://openalex.org/I4210115556","https://openalex.org/I4210155236"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.7785,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.98096699,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"48","issue":"6","first_page":"6771","last_page":"6785"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9781000018119812,"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":0.9781000018119812,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.004800000227987766,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.0031999999191612005,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/matrix-completion","display_name":"Matrix completion","score":0.7217000126838684},{"id":"https://openalex.org/keywords/restricted-isometry-property","display_name":"Restricted isometry property","score":0.6542999744415283},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5418000221252441},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.5131000280380249},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.49939998984336853},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.48559999465942383},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4846000075340271}],"concepts":[{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.7217000126838684},{"id":"https://openalex.org/C17902559","wikidata":"https://www.wikidata.org/wiki/Q17099734","display_name":"Restricted isometry property","level":3,"score":0.6542999744415283},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5859000086784363},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5418000221252441},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.517799973487854},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.5131000280380249},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.49939998984336853},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.48559999465942383},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4846000075340271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4429999887943268},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44179999828338623},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.420199990272522},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.35179999470710754},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.3091999888420105},{"id":"https://openalex.org/C49996920","wikidata":"https://www.wikidata.org/wiki/Q17089185","display_name":"Essential matrix","level":5,"score":0.2939000129699707},{"id":"https://openalex.org/C22629506","wikidata":"https://www.wikidata.org/wiki/Q7602993","display_name":"State-transition matrix","level":4,"score":0.2874000072479248}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2026.3659200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3659200","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:41610361","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41610361","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 pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1621556183","https://openalex.org/W1966661320","https://openalex.org/W1995168330","https://openalex.org/W2047071281","https://openalex.org/W2103972604","https://openalex.org/W2134332047","https://openalex.org/W2144730813","https://openalex.org/W2145962650","https://openalex.org/W2166163936","https://openalex.org/W2167816765","https://openalex.org/W2171046470","https://openalex.org/W2611328865","https://openalex.org/W2774750933","https://openalex.org/W2785436244","https://openalex.org/W2810953629","https://openalex.org/W2962909343","https://openalex.org/W2963831709","https://openalex.org/W2963972677","https://openalex.org/W2971098996","https://openalex.org/W2971507477","https://openalex.org/W3031055522","https://openalex.org/W3080832086","https://openalex.org/W3134510327","https://openalex.org/W3172948607","https://openalex.org/W4220924052","https://openalex.org/W4221135977","https://openalex.org/W4241760093","https://openalex.org/W4312622783","https://openalex.org/W4386736844"],"related_works":[],"abstract_inverted_index":{"The":[0],"problem":[1,72],"of":[2,7,18,29,73,167,182,191],"robust":[3,74,131,196],"matrix":[4,10,14,41,75,132,197],"completion-the":[5],"recovery":[6],"a":[8,12,16,85,96,101,144,156,164,180],"low-rank":[9,111],"and":[11,92,100,112,150],"sparse":[13,113],"from":[15],"sampling":[17,42,57,79],"their":[19],"superposition-has":[20],"been":[21],"addressed":[22],"extensively":[23],"in":[24,38,160],"prior":[25],"literature.":[26],"Yet,":[27],"much":[28],"this":[30,48,83],"work":[31],"has":[32],"focused":[33],"exclusively":[34],"on":[35,172,184],"the":[36,40,71,109,126,176,188,192],"case":[37],"which":[39],"is":[43,50,63,80,90,148],"done":[44],"at":[45],"random,":[46],"as":[47],"scenario":[49],"amenable":[51],"to":[52,67,106,162],"theoretical":[53],"analysis.":[54],"In":[55],"contrast,":[56],"with":[58,95,121,134],"an":[59],"arbitrary":[60,135],"deterministic":[61,78,136],"pattern":[62],"often":[64],"more":[65],"accommodating":[66],"hardware":[68],"implementation;":[69],"consequently,":[70],"completion":[76,133],"under":[77],"considered.":[81],"To":[82],"end,":[84],"restricted":[86],"approximate":[87],"isometry":[88],"property":[89],"proposed":[91,177],"used,":[93],"along":[94],"modified":[97],"golfing":[98],"scheme":[99],"slightly":[102],"strengthened":[103],"incoherence":[104],"condition,":[105],"prove":[107],"that":[108],"latent":[110],"matrices":[114],"are":[115],"uniquely":[116],"recoverable":[117],"via":[118],"convex":[119],"optimization":[120],"asymptotically":[122],"high":[123],"probability,":[124],"providing":[125],"first":[127],"exact-recovery":[128],"theory":[129,178],"for":[130,195],"sampling.":[137],"A":[138],"corresponding":[139],"convex-optimization":[140],"algorithm,":[141],"driven":[142],"by":[143,154],"traditional":[145],"nuclear":[146,158],"norm,":[147],"developed":[149],"then":[151],"subsequently":[152],"generalized":[153,193],"substituting":[155],"convolutional":[157],"norm":[159],"order":[161],"cover":[163],"broader":[165],"range":[166],"application":[168],"scenarios.":[169],"Empirical":[170],"experiments":[171],"synthetic":[173],"data":[174],"verify":[175],"while":[179],"battery":[181],"results":[183],"real-world":[185],"images":[186],"demonstrate":[187],"practical":[189],"efficacy":[190],"algorithm":[194],"recovery.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-01-30T00:00:00"}