{"id":"https://openalex.org/W3185047647","doi":"https://doi.org/10.23919/acc50511.2021.9483436","title":"Online Estimation of Sparse Inverse Covariances","display_name":"Online Estimation of Sparse Inverse Covariances","publication_year":2021,"publication_date":"2021-05-25","ids":{"openalex":"https://openalex.org/W3185047647","doi":"https://doi.org/10.23919/acc50511.2021.9483436","mag":"3185047647"},"language":"en","primary_location":{"id":"doi:10.23919/acc50511.2021.9483436","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc50511.2021.9483436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 American Control Conference (ACC)","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":null,"display_name":"Tong Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tong Yao","raw_affiliation_strings":["School of Electrical and Computer Engineering at Purdue University"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering at Purdue University","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076731201","display_name":"Shreyas Sundaram","orcid":"https://orcid.org/0000-0002-5390-2505"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shreyas Sundaram","raw_affiliation_strings":["School of Electrical and Computer Engineering at Purdue University"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering at Purdue University","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7094,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73133317,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1935","last_page":"1940"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9976000189781189,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9976000189781189,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9976000189781189,"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"}},{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6960588097572327},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6721129417419434},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5401477217674255},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5189208984375},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4958594739437103},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4866541028022766},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.47133755683898926},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4684441387653351},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.44182586669921875},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.42057403922080994},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3968803286552429},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3550342321395874},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3511754870414734},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20955735445022583},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.12883996963500977},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07643094658851624}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6960588097572327},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6721129417419434},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5401477217674255},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5189208984375},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4958594739437103},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4866541028022766},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.47133755683898926},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4684441387653351},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.44182586669921875},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.42057403922080994},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3968803286552429},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3550342321395874},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3511754870414734},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20955735445022583},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.12883996963500977},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07643094658851624},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc50511.2021.9483436","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc50511.2021.9483436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4685253091","display_name":null,"funder_award_id":"CMMI 1638311","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1511986666","https://openalex.org/W1965048988","https://openalex.org/W1976667345","https://openalex.org/W2001667451","https://openalex.org/W2026614436","https://openalex.org/W2081746825","https://openalex.org/W2097581234","https://openalex.org/W2114791779","https://openalex.org/W2116805437","https://openalex.org/W2119980081","https://openalex.org/W2123499997","https://openalex.org/W2132555912","https://openalex.org/W2151128232","https://openalex.org/W2166794017","https://openalex.org/W2475483933","https://openalex.org/W2516118735","https://openalex.org/W2568202645","https://openalex.org/W2593294478","https://openalex.org/W2617467128","https://openalex.org/W2950225911","https://openalex.org/W2962826552","https://openalex.org/W2963364599","https://openalex.org/W2963662204","https://openalex.org/W3098724218","https://openalex.org/W4294651009","https://openalex.org/W6681693836","https://openalex.org/W6682227116","https://openalex.org/W6684415991","https://openalex.org/W6721381422","https://openalex.org/W6766114393"],"related_works":["https://openalex.org/W2788344745","https://openalex.org/W2062336688","https://openalex.org/W2910677864","https://openalex.org/W4300066510","https://openalex.org/W1971337326","https://openalex.org/W2056958800","https://openalex.org/W4213259725","https://openalex.org/W4311388919","https://openalex.org/W1964490787","https://openalex.org/W2060696366"],"abstract_inverted_index":{"Gaussian":[0],"graphical":[1],"models":[2],"have":[3,20],"been":[4,21],"well":[5],"studied":[6],"as":[7,108],"a":[8,36],"way":[9],"to":[10,23,57,83,102],"represent":[11],"the":[12,25,59,85,98,105,109],"relationships":[13],"between":[14,64],"various":[15],"entities,":[16],"and":[17,38,80,114],"numerous":[18],"algorithms":[19,32],"proposed":[22],"learn":[24],"dependencies":[26,63],"in":[27,35,66],"such":[28],"models.":[29],"However,":[30],"these":[31],"process":[33],"data":[34,90,112,129],"batch,":[37],"may":[39],"not":[40],"be":[41],"suitable":[42],"for":[43],"realtime":[44],"estimation.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49,122],"propose":[50],"an":[51,76],"online":[52,99,125],"sparse":[53],"inverse":[54],"covariance":[55],"algorithm":[56,79,126],"infer":[58],"network":[60],"structure":[61],"(i.e.,":[62],"nodes)":[65],"real-time":[67],"from":[68],"time-series":[69],"data.":[70],"Our":[71],"approach":[72],"is":[73],"based":[74],"on":[75,127],"alternating":[77],"minimization":[78],"allows":[81],"users":[82],"select":[84],"number":[86,110],"of":[87,104,111,119],"iterations":[88],"per":[89],"point.":[91],"We":[92],"provide":[93],"theoretical":[94],"guarantees":[95],"showing":[96],"that":[97,103],"estimates":[100],"converge":[101],"batch":[106],"mode":[107],"increases":[113],"characterize":[115],"its":[116],"asymptotic":[117],"rate":[118],"convergence.":[120],"Finally,":[121],"evaluate":[123],"our":[124],"synthetic":[128],"sets.":[130]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}