{"id":"https://openalex.org/W2402228315","doi":"https://doi.org/10.1109/icassp.2016.7472582","title":"Large-scale l&lt;inf&gt;0&lt;/inf&gt; sparse inverse covariance estimation","display_name":"Large-scale l&lt;inf&gt;0&lt;/inf&gt; sparse inverse covariance estimation","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2402228315","doi":"https://doi.org/10.1109/icassp.2016.7472582","mag":"2402228315"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7472582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5018011442","display_name":"Goran Marjanovic","orcid":"https://orcid.org/0000-0003-2016-2384"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Goran Marjanovic","raw_affiliation_strings":["School of Electrical Eng., University of New South Wales, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Eng., University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069292094","display_name":"Magn\u00fas \u00d6. \u00dalfarsson","orcid":"https://orcid.org/0000-0002-0461-040X"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Magnus Ulfarsson","raw_affiliation_strings":["Dept. Electrical Eng., University of Iceland, Reykjavik, Iceland"],"affiliations":[{"raw_affiliation_string":"Dept. Electrical Eng., University of Iceland, Reykjavik, Iceland","institution_ids":["https://openalex.org/I165368041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091154507","display_name":"Victor Solo","orcid":"https://orcid.org/0000-0002-5123-7708"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Victor Solo","raw_affiliation_strings":["Dept. Electrical Eng., University of Iceland, Reykjavik, Iceland"],"affiliations":[{"raw_affiliation_string":"Dept. Electrical Eng., University of Iceland, Reykjavik, Iceland","institution_ids":["https://openalex.org/I165368041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018011442"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":0.6229,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68509648,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4767","last_page":"4771"},"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9993000030517578,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.5571900606155396},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.533854603767395},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5120475888252258},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4762009382247925},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.47219622135162354},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4687393307685852},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4511427879333496},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.422717809677124},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4011181592941284},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39011430740356445},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2341023087501526},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.2199639081954956}],"concepts":[{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.5571900606155396},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.533854603767395},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5120475888252258},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4762009382247925},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.47219622135162354},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4687393307685852},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4511427879333496},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.422717809677124},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4011181592941284},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39011430740356445},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2341023087501526},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.2199639081954956},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7472582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1966661320","https://openalex.org/W1980454827","https://openalex.org/W2010282149","https://openalex.org/W2053186586","https://openalex.org/W2064322097","https://openalex.org/W2068753436","https://openalex.org/W2100556411","https://openalex.org/W2106116051","https://openalex.org/W2107432340","https://openalex.org/W2116805437","https://openalex.org/W2123499997","https://openalex.org/W2125473483","https://openalex.org/W2133396774","https://openalex.org/W2139811697","https://openalex.org/W2146130798","https://openalex.org/W2151128232","https://openalex.org/W2154068876","https://openalex.org/W2396059344","https://openalex.org/W2963364599","https://openalex.org/W3003365835","https://openalex.org/W4238253035","https://openalex.org/W6677437772","https://openalex.org/W6678667221","https://openalex.org/W6678679510","https://openalex.org/W6679719908","https://openalex.org/W6682042988","https://openalex.org/W6682227116","https://openalex.org/W6712392502"],"related_works":["https://openalex.org/W2921280830","https://openalex.org/W2126916073","https://openalex.org/W2887132723","https://openalex.org/W2572601863","https://openalex.org/W2038723318","https://openalex.org/W1679731869","https://openalex.org/W1670628120","https://openalex.org/W3041177925","https://openalex.org/W2886934452","https://openalex.org/W2024369332"],"abstract_inverted_index":{"There":[0],"has":[1],"been":[2],"significant":[3],"interest":[4],"in":[5,10,97],"sparse":[6,24],"inverse":[7,25],"covariance":[8,28],"estimation":[9],"areas":[11],"such":[12],"as":[13],"statistics,":[14],"machine":[15],"learning,":[16],"and":[17,75],"signal":[18],"processing.":[19],"In":[20],"this":[21,104,114,131],"problem,":[22,115],"the":[23,47,51,65,78,84],"of":[26,30],"a":[27,31,108],"matrix":[29,48],"multivariate":[32],"normal":[33],"distribution":[34],"is":[35,43,53,64],"estimated.":[36],"A":[37],"Penalised":[38],"Log-Likelihood":[39],"(PLL)":[40],"optimisation":[41],"problem":[42,91],"solved":[44],"to":[45,73,94],"obtain":[46],"estimator,":[49],"where":[50],"penalty":[52,63],"responsible":[54],"for":[55,81,113,130],"inducing":[56],"sparsity.":[57],"The":[58],"most":[59],"natural":[60],"sparsity":[61],"promoting":[62],"non-convex":[66,85],"l":[67,86],"<sub":[68,87],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[69,88],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</sub>":[70,89],"function.":[71],"Due":[72],"speed":[74],"memory":[76],"limitations,":[77],"existing":[79,128],"algorithms":[80],"dealing":[82],"with":[83],"PLL":[90],"are":[92],"unable":[93],"be":[95],"used":[96],"high":[98],"dimensional":[99],"settings.":[100],"Here":[101],"we":[102],"address":[103],"issue":[105],"by":[106],"presenting":[107],"new":[109],"block":[110],"iterative":[111],"approach":[112,126],"which":[116],"can":[117],"handle":[118],"large-scale":[119],"data":[120],"sizes.":[121],"Simulations":[122],"demonstrate":[123],"that":[124],"our":[125],"outperforms":[127],"methods":[129],"problem.":[132]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}