{"id":"https://openalex.org/W4408354863","doi":"https://doi.org/10.1109/icassp49660.2025.10890766","title":"Large Covariance Matrix Estimation for Groups of Highly Correlated Variables via Nonconvex Optimization","display_name":"Large Covariance Matrix Estimation for Groups of Highly Correlated Variables via Nonconvex Optimization","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408354863","doi":"https://doi.org/10.1109/icassp49660.2025.10890766"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10890766","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890766","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 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/A5005886265","display_name":"Shanshan Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shanshan Zou","raw_affiliation_strings":["ShanghaiTech University,School of Information Science and Technology,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"ShanghaiTech University,School of Information Science and Technology,Shanghai,China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074721617","display_name":"Ziping Zhao","orcid":"https://orcid.org/0000-0002-8668-6263"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziping Zhao","raw_affiliation_strings":["ShanghaiTech University,School of Information Science and Technology,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"ShanghaiTech University,School of Information Science and Technology,Shanghai,China","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005886265"],"corresponding_institution_ids":["https://openalex.org/I30809798"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06381962,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9663000106811523,"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":0.9663000106811523,"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/T10057","display_name":"Face and Expression Recognition","score":0.9643999934196472,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/covariance-matrix","display_name":"Covariance matrix","score":0.743942141532898},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.6148003935813904},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.539769172668457},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5246743559837341},{"id":"https://openalex.org/keywords/cma-es","display_name":"CMA-ES","score":0.5095153450965881},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47642096877098083},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.45270344614982605},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.43989044427871704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4008632004261017},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3781284987926483},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3299618065357208},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0999143123626709},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.06579503417015076}],"concepts":[{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.743942141532898},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.6148003935813904},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.539769172668457},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5246743559837341},{"id":"https://openalex.org/C205555498","wikidata":"https://www.wikidata.org/wiki/Q505588","display_name":"CMA-ES","level":4,"score":0.5095153450965881},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47642096877098083},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.45270344614982605},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.43989044427871704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4008632004261017},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3781284987926483},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3299618065357208},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0999143123626709},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.06579503417015076},{"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10890766","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890766","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320330944","display_name":"Nature","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W216325278","https://openalex.org/W1520752838","https://openalex.org/W1959730594","https://openalex.org/W1965125844","https://openalex.org/W1977556410","https://openalex.org/W1990512452","https://openalex.org/W2057535756","https://openalex.org/W2066218102","https://openalex.org/W2068135051","https://openalex.org/W2072207996","https://openalex.org/W2074682976","https://openalex.org/W2084913894","https://openalex.org/W2087684630","https://openalex.org/W2097515331","https://openalex.org/W2098056745","https://openalex.org/W2101631795","https://openalex.org/W2108864195","https://openalex.org/W2113968881","https://openalex.org/W2114755499","https://openalex.org/W2120636855","https://openalex.org/W2130351130","https://openalex.org/W2147697289","https://openalex.org/W2154514661","https://openalex.org/W2178935672","https://openalex.org/W2508393166","https://openalex.org/W2582533304","https://openalex.org/W2586353914","https://openalex.org/W2912400541","https://openalex.org/W2933407394","https://openalex.org/W2963769637","https://openalex.org/W2963893933","https://openalex.org/W3192454990","https://openalex.org/W4212863985","https://openalex.org/W4386590847","https://openalex.org/W4392931628","https://openalex.org/W4399387526","https://openalex.org/W6683239403"],"related_works":["https://openalex.org/W2572601863","https://openalex.org/W2886934452","https://openalex.org/W2024369332","https://openalex.org/W1976318097","https://openalex.org/W1999545733","https://openalex.org/W4303684144","https://openalex.org/W1626396758","https://openalex.org/W4311761947","https://openalex.org/W2096419081","https://openalex.org/W3103531085"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,12,29,48,50,67,111,115,126,145,160,168],"problem":[4],"of":[5,69,114,121,128],"covariance":[6,30,51,70,83,116],"matrix":[7,31,52],"estimation":[8,68,84,137],"in":[9,75,119],"scenarios":[10],"where":[11],"underlying":[13],"variables":[14,21],"can":[15,53],"be":[16,54],"divided":[17],"into":[18,56],"groups,":[19],"with":[20,92],"within":[22],"each":[23],"group":[24],"being":[25],"highly":[26,42],"correlated.":[27],"Consequently,":[28],"displays":[32],"both":[33,99],"sparse":[34],"and":[35,101],"approximately":[36,58],"low-rank":[37],"characteristics":[38],"due":[39],"to":[40,97,109,164],"these":[41,179],"correlated":[43],"groups.":[44],"By":[45],"appropriately":[46],"rearranging":[47],"variables,":[49],"transformed":[55],"an":[57,141,165],"block":[59],"diagonal":[60],"form.":[61],"In":[62],"this":[63,73,134],"work,":[64],"we":[65,104,139],"investigate":[66],"matrices":[71],"under":[72,172],"structure":[74],"high":[76],"dimensions.":[77],"We":[78,154],"propose":[79],"a":[80,88,93,106,151],"least":[81],"squares-based":[82],"method":[85],"that":[86,158],"incorporates":[87],"trace":[89],"norm":[90],"along":[91],"nonconvex":[94,135],"sparsity":[95],"regularizer":[96],"promote":[98],"low-rankness":[100],"sparsity.":[102],"Additionally,":[103],"introduce":[105],"spectral":[107,130],"constraint":[108],"ensure":[110],"positive":[112],"semi-definiteness":[113],"matrix,":[117],"even":[118],"cases":[120],"finite":[122],"samples,":[123],"while":[124],"permitting":[125],"integration":[127],"prior":[129],"information.":[131],"To":[132],"solve":[133],"statistical":[136,170],"problem,":[138],"develop":[140],"algorithm":[142,162],"based":[143],"on":[144],"majorization-minimization":[146],"framework,":[147],"which":[148],"iteratively":[149],"solves":[150],"convex":[152],"subproblem.":[153],"provide":[155],"theoretical":[156,180],"guarantees":[157],"demonstrate":[159],"proposed":[161],"converges":[163],"estimator":[166],"achieving":[167],"oracle":[169],"rate":[171],"mild":[173],"technical":[174],"conditions.":[175],"Numerical":[176],"experiments":[177],"corroborate":[178],"findings.":[181]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
