{"id":"https://openalex.org/W4289713234","doi":"https://doi.org/10.1109/isit50566.2022.9834858","title":"Mismatched Estimation of Non-Symmetric Rank-One Matrices Under Gaussian Noise","display_name":"Mismatched Estimation of Non-Symmetric Rank-One Matrices Under Gaussian Noise","publication_year":2022,"publication_date":"2022-06-26","ids":{"openalex":"https://openalex.org/W4289713234","doi":"https://doi.org/10.1109/isit50566.2022.9834858"},"language":"en","primary_location":{"id":"doi:10.1109/isit50566.2022.9834858","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834858","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5029483811","display_name":"Farzad Pourkamali","orcid":"https://orcid.org/0000-0002-4585-8348"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Farzad Pourkamali","raw_affiliation_strings":["EPFL,SMILS,Lausanne,Switzerland","SMILS, EPFL, Lausanne, Switzerland"],"affiliations":[{"raw_affiliation_string":"EPFL,SMILS,Lausanne,Switzerland","institution_ids":["https://openalex.org/I5124864"]},{"raw_affiliation_string":"SMILS, EPFL, Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038854134","display_name":"Nicolas Macris","orcid":"https://orcid.org/0000-0003-2189-7411"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Nicolas Macris","raw_affiliation_strings":["EPFL,SMILS,Lausanne,Switzerland","SMILS, EPFL, Lausanne, Switzerland"],"affiliations":[{"raw_affiliation_string":"EPFL,SMILS,Lausanne,Switzerland","institution_ids":["https://openalex.org/I5124864"]},{"raw_affiliation_string":"SMILS, EPFL, Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029483811"],"corresponding_institution_ids":["https://openalex.org/I5124864"],"apc_list":null,"apc_paid":null,"fwci":3.8016,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.94559585,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1288","last_page":"1293"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9983999729156494,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9739000201225281,"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/rank","display_name":"Rank (graph theory)","score":0.6735090017318726},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6619237065315247},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5842056274414062},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5654662847518921},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5076268911361694},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4995574951171875},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4146175980567932},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.39987069368362427},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3974577784538269},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.37354639172554016},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2752946615219116},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.24315086007118225},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12800106406211853},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10982513427734375}],"concepts":[{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6735090017318726},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6619237065315247},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5842056274414062},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5654662847518921},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5076268911361694},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4995574951171875},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4146175980567932},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.39987069368362427},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3974577784538269},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.37354639172554016},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2752946615219116},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.24315086007118225},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12800106406211853},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10982513427734375},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit50566.2022.9834858","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834858","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1922029667","https://openalex.org/W2040969041","https://openalex.org/W2085610073","https://openalex.org/W2086177078","https://openalex.org/W2087016193","https://openalex.org/W2101513535","https://openalex.org/W2111616148","https://openalex.org/W2132657058","https://openalex.org/W2136135636","https://openalex.org/W2148136784","https://openalex.org/W2431536272","https://openalex.org/W2588219153","https://openalex.org/W2605304986","https://openalex.org/W2811244594","https://openalex.org/W2913003253","https://openalex.org/W2963765569","https://openalex.org/W3016604095","https://openalex.org/W3098500246","https://openalex.org/W3099044538","https://openalex.org/W3104469760","https://openalex.org/W3104705077","https://openalex.org/W3199549745","https://openalex.org/W3206621305","https://openalex.org/W4223583446","https://openalex.org/W4229746864","https://openalex.org/W4287072661","https://openalex.org/W4289713234","https://openalex.org/W6735974756","https://openalex.org/W6798776280","https://openalex.org/W6801661698","https://openalex.org/W6802607899","https://openalex.org/W6810377618"],"related_works":["https://openalex.org/W2112835755","https://openalex.org/W4291951920","https://openalex.org/W2576994247","https://openalex.org/W2608353378","https://openalex.org/W2349674371","https://openalex.org/W2097495471","https://openalex.org/W1970319972","https://openalex.org/W2572355887","https://openalex.org/W2953254336","https://openalex.org/W2112030392"],"abstract_inverted_index":{"We":[0,33,55],"consider":[1],"the":[2,43,57,62,69,75,89,97,112,120,138,146],"estimation":[3,92],"of":[4,47,78,109,123],"a":[5,23,35,106],"n\u00d7m":[6],"matrix":[7],"u":[8],"<sup":[9,13],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[10,14],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u2217</sup>":[11],"v":[12],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u2217T</sup>":[15],"observed":[16],"through":[17],"an":[18,52],"additive":[19,82],"Gaussian":[20,79],"noise":[21],"channel,":[22],"problem":[24],"that":[25,87],"frequently":[26],"arises":[27],"in":[28,41,68,88],"statistics":[29],"and":[30,50,81],"machine":[31],"learning.":[32],"investigate":[34],"scenario":[36],"involving":[37],"mismatched":[38,90],"Bayesian":[39],"inference":[40],"which":[42],"statistician":[44],"is":[45,93,117],"unaware":[46],"true":[48,139],"prior":[49,140],"uses":[51],"assumed":[53,148],"prior.":[54,149],"derive":[56],"exact":[58],"analytic":[59],"expression":[60],"for":[61,74,126,137,145],"asymptotic":[63,121],"mean":[64],"squared":[65],"error":[66],"(MSE)":[67],"large":[70],"system":[71],"size":[72],"limit":[73],"particular":[76],"case":[77],"priors":[80],"noise.":[83],"Our":[84,115,129],"formulas":[85],"demonstrate":[86],"case,":[91],"still":[94],"possible.":[95],"Additionally,":[96],"minimum":[98],"MSE":[99],"(MMSE)":[100],"can":[101,131],"be":[102,132],"obtained":[103],"by":[104],"selecting":[105],"non-trivial":[107],"set":[108],"parameters":[110],"beyond":[111],"matched":[113],"parameters.":[114],"technique":[116],"based":[118],"on":[119],"behavior":[122],"spherical":[124],"integrals":[125],"rectangular":[127],"matrices.":[128],"method":[130],"extended":[133],"to":[134],"non-rotation-invariant":[135],"distributions":[136],"but":[141],"requires":[142],"rotation":[143],"invariance":[144],"statistician\u2019s":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}
