{"id":"https://openalex.org/W2889099799","doi":"https://doi.org/10.1109/ssp.2018.8450790","title":"An \u2113<sub>1</sub>-Penalization Of Adaptive Normalized Quasi-Newton Algorithm For Sparsity-Aware Generalized Eigenvector Estimation","display_name":"An \u2113<sub>1</sub>-Penalization Of Adaptive Normalized Quasi-Newton Algorithm For Sparsity-Aware Generalized Eigenvector Estimation","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2889099799","doi":"https://doi.org/10.1109/ssp.2018.8450790","mag":"2889099799"},"language":"en","primary_location":{"id":"doi:10.1109/ssp.2018.8450790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2018.8450790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Statistical Signal Processing Workshop (SSP)","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/A5081724559","display_name":"Kengo Uchida","orcid":null},"institutions":[{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]},{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kengo Uchida","raw_affiliation_strings":["Department of Information and Communications Engineering, Tokyo Institute of Technology, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communications Engineering, Tokyo Institute of Technology, Japan","institution_ids":["https://openalex.org/I90023481","https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103022814","display_name":"Isao Yamada","orcid":"https://orcid.org/0000-0002-6563-7526"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]},{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Isao Yamada","raw_affiliation_strings":["Department of Information and Communications Engineering, Tokyo Institute of Technology, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communications Engineering, Tokyo Institute of Technology, Japan","institution_ids":["https://openalex.org/I90023481","https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081724559"],"corresponding_institution_ids":["https://openalex.org/I114531698","https://openalex.org/I90023481"],"apc_list":null,"apc_paid":null,"fwci":0.4054,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59271452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"11","issue":null,"first_page":"528","last_page":"532"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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":0.9998000264167786,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9994999766349792,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.7367647886276245},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6505986452102661},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5533485412597656},{"id":"https://openalex.org/keywords/matrix-pencil","display_name":"Matrix pencil","score":0.5283915400505066},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5086444616317749},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.45504558086395264},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4332123100757599},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4147277772426605},{"id":"https://openalex.org/keywords/eigendecomposition-of-a-matrix","display_name":"Eigendecomposition of a matrix","score":0.411782443523407},{"id":"https://openalex.org/keywords/generalized-eigenvector","display_name":"Generalized eigenvector","score":0.4110979437828064},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4059414863586426},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4037027657032013},{"id":"https://openalex.org/keywords/symmetric-matrix","display_name":"Symmetric matrix","score":0.27830564975738525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22393575310707092}],"concepts":[{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.7367647886276245},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6505986452102661},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5533485412597656},{"id":"https://openalex.org/C1576492","wikidata":"https://www.wikidata.org/wiki/Q3739929","display_name":"Matrix pencil","level":3,"score":0.5283915400505066},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5086444616317749},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.45504558086395264},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4332123100757599},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4147277772426605},{"id":"https://openalex.org/C169756996","wikidata":"https://www.wikidata.org/wiki/Q194919","display_name":"Eigendecomposition of a matrix","level":3,"score":0.411782443523407},{"id":"https://openalex.org/C147925508","wikidata":"https://www.wikidata.org/wiki/Q970767","display_name":"Generalized eigenvector","level":5,"score":0.4110979437828064},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4059414863586426},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4037027657032013},{"id":"https://openalex.org/C54848796","wikidata":"https://www.wikidata.org/wiki/Q339011","display_name":"Symmetric matrix","level":3,"score":0.27830564975738525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22393575310707092},{"id":"https://openalex.org/C22629506","wikidata":"https://www.wikidata.org/wiki/Q7602993","display_name":"State-transition matrix","level":4,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssp.2018.8450790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2018.8450790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Statistical Signal Processing Workshop (SSP)","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":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W292716351","https://openalex.org/W1492221128","https://openalex.org/W1975900269","https://openalex.org/W1977899734","https://openalex.org/W1979817396","https://openalex.org/W1990701162","https://openalex.org/W2007527993","https://openalex.org/W2044809283","https://openalex.org/W2097417531","https://openalex.org/W2104309817","https://openalex.org/W2111281053","https://openalex.org/W2115755118","https://openalex.org/W2133515443","https://openalex.org/W2139182243","https://openalex.org/W2145211141","https://openalex.org/W2166604943","https://openalex.org/W2271854708","https://openalex.org/W3014542904","https://openalex.org/W6750968397"],"related_works":["https://openalex.org/W2051710799","https://openalex.org/W2117760611","https://openalex.org/W4360902178","https://openalex.org/W1588685507","https://openalex.org/W2369173090","https://openalex.org/W3168844238","https://openalex.org/W2782188726","https://openalex.org/W2122156222","https://openalex.org/W2531843432","https://openalex.org/W2470499989"],"abstract_inverted_index":{"The":[0],"goal":[1],"of":[2,29,46],"this":[3],"paper":[4],"is":[5,68,104],"to":[6],"establish":[7],"a":[8,55],"widely":[9],"applicable":[10],"method":[11],"for":[12,71,106],"exploiting":[13],"the":[14,30,44,47,50,72,82,86,91,94],"sparsity":[15,42],"in":[16,43,90],"generalized":[17,48,101],"eigenvector":[18,102,109],"estimation.":[19],"We":[20],"propose":[21],"an":[22],"\u2113":[23,60],"<sub":[24,61],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[25,62],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[26,63],"-penalized":[27],"extension":[28],"Adaptive":[31],"normalized":[32],"quasi-Newton":[33],"algorithm":[34,53,74,84],"(Nguyen":[35],"and":[36,103],"Yamada,":[37],"2013":[38],".":[39],"To":[40],"enhance":[41],"estimate":[45],"eigenvector,":[49],"proposed":[51,73,83],"adaptive":[52],"maximizes":[54],"certain":[56],"non-convex":[57],"criterion":[58],"with":[59,75],"penalty.":[64],"A":[65],"convergence":[66],"analysis":[67],"also":[69],"given":[70],"decaying":[76],"weight.":[77],"Numerical":[78],"experiments":[79],"show":[80],"that":[81],"improves":[85],"subspace":[87],"tracking":[88],"performance":[89],"situation":[92],"where":[93],"covariance":[95],"matrix":[96],"pencil":[97],"has":[98],"sparse":[99,112],"principal":[100],"effective":[105],"recent":[107],"sparsity-aware":[108],"analysis,":[110],"e.g.,":[111],"PCA.":[113]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
