{"id":"https://openalex.org/W2921505969","doi":"https://doi.org/10.23919/apsipa.2018.8659569","title":"A Nested &lt;tex&gt;$\\ell_{1}$&lt;/tex&gt;-penalized Adaptive Normalized Quasi-Newton Algorithm for Sparsity-Aware Generalized Eigen-subspace Extraction","display_name":"A Nested &lt;tex&gt;$\\ell_{1}$&lt;/tex&gt;-penalized Adaptive Normalized Quasi-Newton Algorithm for Sparsity-Aware Generalized Eigen-subspace Extraction","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2921505969","doi":"https://doi.org/10.23919/apsipa.2018.8659569","mag":"2921505969"},"language":"en","primary_location":{"id":"doi:10.23919/apsipa.2018.8659569","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/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":["Tokyo Institute of Technology, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Japan","institution_ids":["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"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Isao Yamada","raw_affiliation_strings":["Tokyo Institute of Technology, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Japan","institution_ids":["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"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19392191,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"212","last_page":"217"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9986000061035156,"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":0.9980999827384949,"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/orthogonality","display_name":"Orthogonality","score":0.7923848628997803},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7116837501525879},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6861250400543213},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6539336442947388},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.5438788533210754},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.48188143968582153},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4691919982433319},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.4391041398048401},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3954382836818695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3753759264945984},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.09452188014984131}],"concepts":[{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.7923848628997803},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7116837501525879},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6861250400543213},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6539336442947388},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.5438788533210754},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.48188143968582153},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4691919982433319},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.4391041398048401},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3954382836818695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3753759264945984},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.09452188014984131},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.0},{"id":"https://openalex.org/C188082640","wikidata":"https://www.wikidata.org/wiki/Q1780899","display_name":"Complementation","level":4,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/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},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/apsipa.2018.8659569","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1492221128","https://openalex.org/W1975900269","https://openalex.org/W1977899734","https://openalex.org/W1979817396","https://openalex.org/W1981784004","https://openalex.org/W1990701162","https://openalex.org/W1999542175","https://openalex.org/W2001951724","https://openalex.org/W2044809283","https://openalex.org/W2097417531","https://openalex.org/W2104309817","https://openalex.org/W2111281053","https://openalex.org/W2113600901","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/W2763846745","https://openalex.org/W2889099799","https://openalex.org/W2963514887","https://openalex.org/W3014542904","https://openalex.org/W4297584953","https://openalex.org/W6728913925"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W2806259446","https://openalex.org/W2963326959","https://openalex.org/W2388968854","https://openalex.org/W1985318690"],"abstract_inverted_index":{"The":[0],"sparsity-aware":[1],"generalized":[2,51,58],"eigen-subspace":[3],"extraction":[4],"is":[5,60],"a":[6],"modern":[7],"strategy":[8],"to":[9,63],"achieve":[10],"better":[11],"interpretability":[12],"than":[13],"classical":[14],"statistical":[15],"data":[16,37],"analysis,":[17],"and":[18,27,36,107],"has":[19],"been":[20,81],"realized,":[21],"as":[22],"sparse":[23,25,28],"PCA,":[24],"CCA":[26],"FDA,":[29],"etc,":[30],"in":[31,43,66],"signal":[32,48],"processing,":[33,49],"machine":[34],"learning":[35,68,76],"sciences.":[38],"For":[39],"its":[40],"broader":[41],"applications":[42],"the":[44,50,54,67,94],"scenarios":[45],"of":[46,56,96],"adaptive":[47,75,102],"orthogonality":[52],"among":[53],"estimates":[55],"principal":[57],"eigenvectors":[59],"certainly":[61],"desired":[62],"be":[64],"exploited":[65],"process.":[69],"However,":[70],"it":[71],"seems":[72],"that":[73],"such":[74],"algorithms":[77],"have":[78],"not":[79],"yet":[80],"reported":[82],"so":[83],"far.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88],"present":[89],"an":[90],"algorithm":[91,105],"by":[92],"combining":[93],"idea":[95],"\u2113":[97],"<sub":[98],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[99],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[100],"-penalized":[101],"normalized":[103],"quasi-Newton":[104],"(Uchida":[106],"Yamada,":[108],"2018)":[109],"with":[110],"Nested":[111],"orthogonal":[112],"complement":[113],"structure":[114],"(NTY":[115],"2013,":[116],"KYY":[117],"2017).":[118]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
