{"id":"https://openalex.org/W2564550895","doi":"https://doi.org/10.1109/eusipco.2016.7760452","title":"Mean field analysis of sparse reconstruction with correlated variables","display_name":"Mean field analysis of sparse reconstruction with correlated variables","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2564550895","doi":"https://doi.org/10.1109/eusipco.2016.7760452","mag":"2564550895"},"language":"en","primary_location":{"id":"doi:10.1109/eusipco.2016.7760452","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eusipco.2016.7760452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 24th European Signal Processing Conference (EUSIPCO)","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/A5031925884","display_name":"Mohammad Ramezanali","orcid":"https://orcid.org/0000-0003-0039-2043"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Ramezanali","raw_affiliation_strings":["Department of Physics and Astronomy, Rutgers University, Piscataway, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics and Astronomy, Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037732748","display_name":"Partha P. Mitra","orcid":"https://orcid.org/0000-0001-8818-6804"},"institutions":[{"id":"https://openalex.org/I2750212522","display_name":"Cold Spring Harbor Laboratory","ror":"https://ror.org/02qz8b764","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2750212522"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Partha P. Mitra","raw_affiliation_strings":["Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA","institution_ids":["https://openalex.org/I2750212522"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066552315","display_name":"Anirvan M. Sengupta","orcid":"https://orcid.org/0000-0001-8485-0018"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anirvan M. Sengupta","raw_affiliation_strings":["Department of Physics and Astronomy, Rutgers University, Piscataway, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics and Astronomy, Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5327,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67098921,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"9","issue":null,"first_page":"1267","last_page":"1271"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9955999851226807,"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"}},{"id":"https://openalex.org/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/boundary","display_name":"Boundary (topology)","score":0.4728717505931854},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45678457617759705},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43576574325561523},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.43220779299736023},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.42223894596099854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3937492072582245},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.38455185294151306},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30213141441345215},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.11897829174995422},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08603513240814209}],"concepts":[{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4728717505931854},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45678457617759705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43576574325561523},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.43220779299736023},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.42223894596099854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3937492072582245},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.38455185294151306},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30213141441345215},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.11897829174995422},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08603513240814209}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/eusipco.2016.7760452","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eusipco.2016.7760452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 24th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.cshl.edu:40144","is_oa":false,"landing_page_url":"http://repository.cshl.edu/id/eprint/40144/","pdf_url":null,"source":{"id":"https://openalex.org/S4306402288","display_name":"Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2750212522","host_organization_name":"Cold Spring Harbor Laboratory","host_organization_lineage":["https://openalex.org/I2750212522"],"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":"Conference or Workshop Item"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6700000166893005,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1981051810","https://openalex.org/W1989132237","https://openalex.org/W2010669260","https://openalex.org/W2015418199","https://openalex.org/W2029559556","https://openalex.org/W2040912306","https://openalex.org/W2044762091","https://openalex.org/W2050834445","https://openalex.org/W2054184486","https://openalex.org/W2082029531","https://openalex.org/W2090842051","https://openalex.org/W2098012923","https://openalex.org/W2103955025","https://openalex.org/W2109357213","https://openalex.org/W2122825543","https://openalex.org/W2127271355","https://openalex.org/W2129755576","https://openalex.org/W2135046866","https://openalex.org/W2139053635","https://openalex.org/W2145096794","https://openalex.org/W2163916252","https://openalex.org/W3101699044","https://openalex.org/W3102670196","https://openalex.org/W3121195152","https://openalex.org/W4206502013"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2358292267","https://openalex.org/W2157715872","https://openalex.org/W2150755939"],"abstract_inverted_index":{"Sparse":[0],"reconstruction":[1],"algorithms":[2],"aim":[3],"to":[4,97],"retrieve":[5],"high-dimensional":[6],"sparse":[7,59,138],"signals":[8],"from":[9,94],"a":[10,32,43,57,64],"limited":[11],"number":[12],"of":[13,56,74,78,86,153],"measurements.":[14],"A":[15],"common":[16],"example":[17],"is":[18,25,61,105,109],"LASSO":[19],"or":[20],"Basis":[21],"Pursuit":[22],"where":[23,53,67,140],"sparsity":[24],"enforced":[26],"using":[27],"an":[28,101],"\u21131-penalty":[29],"together":[30],"with":[31,114,121],"cost":[33],"function":[34],"||y":[35],"-":[36],"Hx||22.":[37],"For":[38],"random":[39],"design":[40],"matrices":[41],"H,":[42],"sharp":[44],"phase":[45,75],"transition":[46,76],"boundary":[47,77],"separates":[48],"the":[49,68,79,115,125,136,150],"`good'":[50],"parameter":[51],"region":[52],"error-free":[54],"recovery":[55,69,127],"sufficiently":[58],"signal":[60,103],"possible":[62],"and":[63,107],"`bad'":[65],"regime":[66],"fails.":[70],"However,":[71],"theoretical":[72],"analysis":[73],"correlated":[80],"variables":[81],"case":[82],"lags":[83],"behind":[84],"that":[85,99],"uncorrelated":[87],"variables.":[88],"Here":[89],"we":[90],"use":[91],"replica":[92],"trick":[93],"statistical":[95],"physics":[96],"show":[98],"when":[100],"N-dimensional":[102],"x":[104],"K-sparse":[106],"H":[108],"M":[110,130],"\u00d7":[111],"N":[112],"dimensional":[113],"covariance":[116],"E[HiaHjb]":[117],"=":[118],"1/M":[119],"CijDab,":[120],"all":[122],"Daa=":[123],"1,":[124,143],"perfect":[126],"occurs":[128],"at":[129],"~":[131],"\u03c8K(D)":[132,141],"K":[133],"log(N/M)":[134],"in":[135],"very":[137],"limit,":[139],"\u2265":[142],"indicating":[144],"need":[145],"for":[146,149],"more":[147],"observations":[148],"same":[151],"degree":[152],"sparsity.":[154]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
