{"id":"https://openalex.org/W2498838870","doi":"https://doi.org/10.1109/tsp.2016.2597121","title":"Relevance Singular Vector Machine for Low-Rank Matrix Reconstruction","display_name":"Relevance Singular Vector Machine for Low-Rank Matrix Reconstruction","publication_year":2016,"publication_date":"2016-08-02","ids":{"openalex":"https://openalex.org/W2498838870","doi":"https://doi.org/10.1109/tsp.2016.2597121","mag":"2498838870"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2016.2597121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2016.2597121","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":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-193155","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074161005","display_name":"Martin Sundin","orcid":"https://orcid.org/0000-0001-6992-5771"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Martin Sundin","raw_affiliation_strings":["ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057105677","display_name":"Cristian R. Rojas","orcid":"https://orcid.org/0000-0003-0355-2663"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Cristian R. Rojas","raw_affiliation_strings":["ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019386542","display_name":"Magnus Jansson","orcid":"https://orcid.org/0000-0002-6855-5868"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Magnus Jansson","raw_affiliation_strings":["ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101692633","display_name":"Saikat Chatterjee","orcid":"https://orcid.org/0000-0003-2638-6047"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Saikat Chatterjee","raw_affiliation_strings":["ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3088,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.61512289,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"64","issue":"20","first_page":"5327","last_page":"5339"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9966999888420105,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9965999722480774,"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/rank","display_name":"Rank (graph theory)","score":0.6413471102714539},{"id":"https://openalex.org/keywords/kronecker-delta","display_name":"Kronecker delta","score":0.5730291604995728},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.553882360458374},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5233097076416016},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48689189553260803},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4846106469631195},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4725739061832428},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4688958525657654},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.4675620496273041},{"id":"https://openalex.org/keywords/singular-value","display_name":"Singular value","score":0.45429128408432007},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4157297611236572},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.40922677516937256},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4089665114879608},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40287312865257263},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3910720646381378},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.388751745223999},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.2912099361419678},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1457238495349884}],"concepts":[{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6413471102714539},{"id":"https://openalex.org/C39482219","wikidata":"https://www.wikidata.org/wiki/Q192826","display_name":"Kronecker delta","level":2,"score":0.5730291604995728},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.553882360458374},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5233097076416016},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48689189553260803},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4846106469631195},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4725739061832428},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4688958525657654},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.4675620496273041},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.45429128408432007},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4157297611236572},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.40922677516937256},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4089665114879608},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40287312865257263},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3910720646381378},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.388751745223999},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.2912099361419678},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1457238495349884},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","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/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2016.2597121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2016.2597121","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:DiVA.org:kth-193155","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-193155","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article in journal"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:kth-193155","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-193155","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article in journal"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G7038735060","display_name":null,"funder_award_id":"2015-05484","funder_id":"https://openalex.org/F4320322581","funder_display_name":"Vetenskapsr\u00e5det"}],"funders":[{"id":"https://openalex.org/F4320322581","display_name":"Vetenskapsr\u00e5det","ror":"https://ror.org/03zttf063"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1601795611","https://openalex.org/W1607198972","https://openalex.org/W1633751774","https://openalex.org/W1663973292","https://openalex.org/W1863732927","https://openalex.org/W1988520084","https://openalex.org/W2016715139","https://openalex.org/W2030769153","https://openalex.org/W2033419225","https://openalex.org/W2044902835","https://openalex.org/W2047071281","https://openalex.org/W2047102900","https://openalex.org/W2049633694","https://openalex.org/W2073681337","https://openalex.org/W2077430220","https://openalex.org/W2085040216","https://openalex.org/W2085937320","https://openalex.org/W2091472131","https://openalex.org/W2097714737","https://openalex.org/W2103972604","https://openalex.org/W2118034806","https://openalex.org/W2121154640","https://openalex.org/W2134332047","https://openalex.org/W2137245235","https://openalex.org/W2141159272","https://openalex.org/W2146000945","https://openalex.org/W2158923808","https://openalex.org/W2164452299","https://openalex.org/W2535123820","https://openalex.org/W2611328865","https://openalex.org/W2963049629","https://openalex.org/W2963762195","https://openalex.org/W2974222084","https://openalex.org/W3102122544","https://openalex.org/W3140968660","https://openalex.org/W3179903767","https://openalex.org/W4211150925","https://openalex.org/W4232980324","https://openalex.org/W4285719527","https://openalex.org/W6636690510","https://openalex.org/W6639038035","https://openalex.org/W6684945375","https://openalex.org/W6728872801","https://openalex.org/W7070499600"],"related_works":["https://openalex.org/W2952489973","https://openalex.org/W2106005123","https://openalex.org/W4300776969","https://openalex.org/W2266965707","https://openalex.org/W2108753466","https://openalex.org/W2084983808","https://openalex.org/W2906317811","https://openalex.org/W2241093516","https://openalex.org/W4318564253","https://openalex.org/W2402491700"],"abstract_inverted_index":{"We":[0,35],"develop":[1],"Bayesian":[2,41],"learning":[3],"methods":[4,19,78],"for":[5],"low-rank":[6,21,44],"matrix":[7],"reconstruction":[8],"and":[9,43,87],"completion":[10],"from":[11],"linear":[12],"measurements.":[13],"For":[14],"under-determined":[15],"systems,":[16],"the":[17,25,28,39,51,63,71,77],"developed":[18],"reconstruct":[20],"matrices":[22,57],"when":[23],"neither":[24],"rank":[26],"nor":[27],"noise":[29],"power":[30],"is":[31,79],"known":[32],"a":[33,59],"priori.":[34],"derive":[36],"relations":[37,49],"between":[38],"proposed":[40],"models":[42],"promoting":[45],"penalty":[46],"functions.":[47],"The":[48,74],"justify":[50],"use":[52,66],"of":[53,76],"Kronecker":[54],"structured":[55],"covariance":[56],"in":[58],"Gaussian-based":[60],"prior.":[61],"In":[62],"methods,":[64],"we":[65],"expectation":[67],"maximization":[68],"to":[69],"learn":[70],"model":[72],"parameters.":[73],"performance":[75],"evaluated":[80],"through":[81],"extensive":[82],"numerical":[83],"simulations":[84],"on":[85],"synthetic":[86],"real":[88],"data.":[89]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}