{"id":"https://openalex.org/W2067157583","doi":"https://doi.org/10.1109/icassp.2014.6855092","title":"Estimation of simultaneously structured covariance matrices from quadratic measurements","display_name":"Estimation of simultaneously structured covariance matrices from quadratic measurements","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2067157583","doi":"https://doi.org/10.1109/icassp.2014.6855092","mag":"2067157583"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2014.6855092","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6855092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100416078","display_name":"Yuxin Chen","orcid":"https://orcid.org/0000-0001-9256-5815"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxin Chen","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University","[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053809095","display_name":"Yuejie Chi","orcid":"https://orcid.org/0000-0002-6766-5459"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuejie Chi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Ohio State University","Dept. of Electr. & Comput. Eng., Ohio state Univ., Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Ohio State University","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Ohio state Univ., Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074116801","display_name":"Andrea Goldsmith","orcid":"https://orcid.org/0000-0001-5686-800X"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrea J. Goldsmith","raw_affiliation_strings":["Stanford University, Stanford, CA, US","[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA, US","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7669","last_page":"7673"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T11183","display_name":"Advanced X-ray Imaging Techniques","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.7900171279907227},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.6951978206634521},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5960286259651184},{"id":"https://openalex.org/keywords/covariance-intersection","display_name":"Covariance intersection","score":0.5940186977386475},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5911593437194824},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.5618405342102051},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5455091595649719},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.5067773461341858},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4641472101211548},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.46252283453941345},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44184327125549316},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.43821579217910767},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4313570261001587},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.4138803482055664},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3443818688392639},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1362697184085846},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13155648112297058},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12766006588935852}],"concepts":[{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.7900171279907227},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.6951978206634521},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5960286259651184},{"id":"https://openalex.org/C83042196","wikidata":"https://www.wikidata.org/wiki/Q5178898","display_name":"Covariance intersection","level":4,"score":0.5940186977386475},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5911593437194824},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.5618405342102051},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5455091595649719},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.5067773461341858},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4641472101211548},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.46252283453941345},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44184327125549316},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.43821579217910767},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4313570261001587},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.4138803482055664},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3443818688392639},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1362697184085846},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13155648112297058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12766006588935852},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2014.6855092","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6855092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1972822190","https://openalex.org/W1989008275","https://openalex.org/W1998937355","https://openalex.org/W2007593159","https://openalex.org/W2037653617","https://openalex.org/W2044809283","https://openalex.org/W2067638548","https://openalex.org/W2078397124","https://openalex.org/W2079360231","https://openalex.org/W2083346837","https://openalex.org/W2090287842","https://openalex.org/W2091775960","https://openalex.org/W2101792886","https://openalex.org/W2107820823","https://openalex.org/W2110355775","https://openalex.org/W2117497535","https://openalex.org/W2133105246","https://openalex.org/W2142901448","https://openalex.org/W2145096794","https://openalex.org/W2155434899","https://openalex.org/W2167850383","https://openalex.org/W2169501582","https://openalex.org/W2296616510","https://openalex.org/W2952040794","https://openalex.org/W2963241021","https://openalex.org/W2963855280","https://openalex.org/W3148325197","https://openalex.org/W4250955649","https://openalex.org/W4299429707"],"related_works":["https://openalex.org/W2126916073","https://openalex.org/W2022823194","https://openalex.org/W1974588588","https://openalex.org/W2572601863","https://openalex.org/W1489099099","https://openalex.org/W4234846126","https://openalex.org/W2118568436","https://openalex.org/W2018001152","https://openalex.org/W1678480493","https://openalex.org/W2169046449"],"abstract_inverted_index":{"This":[0],"paper":[1],"explores":[2],"covariance":[3,26,77],"estimation":[4],"from":[5,52],"energy":[6],"measurements":[7,93],"that":[8],"are":[9,138],"collected":[10],"via":[11],"a":[12,36,53,129],"quadratic":[13],"form":[14],"of":[15,56,75,92,132],"measurement":[16,133],"vectors.":[17],"A":[18],"popular":[19],"structural":[20,67],"model":[21],"is":[22,60,100],"considered":[23],"where":[24],"the":[25,72,76,90,95,106,113],"matrices":[27],"possess":[28],"low-rank":[29],"and":[30,49,65,111,123,135],"sparse":[31,103,122],"structures":[32],"simultaneously.":[33],"We":[34],"investigate":[35],"weighted":[37],"convex":[38],"relaxation":[39],"algorithm":[40,59,83],"tailored":[41],"for":[42],"this":[43],"joint":[44],"structure,":[45],"which":[46],"guarantees":[47,116],"exact":[48,85],"universal":[50],"recovery":[51,86],"small":[54],"number":[55,91],"measurements.":[57],"The":[58],"also":[61],"robust":[62],"against":[63],"noise":[64],"imperfect":[66],"assumptions.":[68],"In":[69],"particular,":[70],"when":[71],"non-zero":[73],"entries":[74],"matrix":[78],"exhibit":[79],"power-law":[80],"decay,":[81],"our":[82,136],"admits":[84],"as":[87,89,126,128],"soon":[88],"exceeds":[94],"theoretic":[96],"limit.":[97],"Our":[98],"method":[99],"related":[101],"to":[102,120],"phase":[104],"retrieval:":[105],"analysis":[107,143],"framework":[108],"herein":[109],"recovers":[110],"strengthens":[112],"best-known":[114],"performance":[115],"by":[117],"extending":[118],"them":[119],"approximately":[121],"noisy":[124],"scenarios":[125],"well":[127],"broader":[130],"class":[131],"vectors,":[134],"results":[137],"derived":[139],"using":[140],"much":[141],"simpler":[142],"methods.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}