{"id":"https://openalex.org/W2098385363","doi":"https://doi.org/10.1109/tsp.2008.2006587","title":"Sparse Variable PCA Using Geodesic Steepest Descent","display_name":"Sparse Variable PCA Using Geodesic Steepest Descent","publication_year":2008,"publication_date":"2008-10-07","ids":{"openalex":"https://openalex.org/W2098385363","doi":"https://doi.org/10.1109/tsp.2008.2006587","mag":"2098385363"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2008.2006587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2008.2006587","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-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/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"]},{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["IS","US"],"is_corresponding":false,"raw_author_name":"M.O. Ulfarsson","raw_affiliation_strings":["Department of Electrical Engineering, University of Iceland, Reykjavik, Iceland","[Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Iceland, Reykjavik, Iceland","institution_ids":["https://openalex.org/I165368041"]},{"raw_affiliation_string":"[Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI]","institution_ids":["https://openalex.org/I27837315"]}]},{"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/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"V. Solo","raw_affiliation_strings":["School of Electrical Engineering, University of New South Wales, Sydney, NSW, Australia","[School of Electrical Engineering, University of New South Wales, Sydney, NSW, Australia]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"[School of Electrical Engineering, University of New South Wales, Sydney, NSW, Australia]","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":2.7511,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.89583992,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"56","issue":"12","first_page":"5823","last_page":"5832"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9959999918937683,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9959999918937683,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9922000169754028,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.7359564304351807},{"id":"https://openalex.org/keywords/sparse-pca","display_name":"Sparse PCA","score":0.7201234102249146},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6420159339904785},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5643038749694824},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5336464643478394},{"id":"https://openalex.org/keywords/bayesian-information-criterion","display_name":"Bayesian information criterion","score":0.4979381561279297},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4970274269580841},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.49352753162384033},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4779510498046875},{"id":"https://openalex.org/keywords/coordinate-descent","display_name":"Coordinate descent","score":0.4527934789657593},{"id":"https://openalex.org/keywords/design-matrix","display_name":"Design matrix","score":0.4364890456199646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4255621135234833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3984636068344116},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.27214697003364563},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21363374590873718},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.16741546988487244}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7359564304351807},{"id":"https://openalex.org/C24252448","wikidata":"https://www.wikidata.org/wiki/Q7573786","display_name":"Sparse PCA","level":3,"score":0.7201234102249146},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6420159339904785},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5643038749694824},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5336464643478394},{"id":"https://openalex.org/C168136583","wikidata":"https://www.wikidata.org/wiki/Q1988242","display_name":"Bayesian information criterion","level":2,"score":0.4979381561279297},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4970274269580841},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.49352753162384033},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4779510498046875},{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.4527934789657593},{"id":"https://openalex.org/C203233044","wikidata":"https://www.wikidata.org/wiki/Q5264358","display_name":"Design matrix","level":3,"score":0.4364890456199646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4255621135234833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3984636068344116},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.27214697003364563},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21363374590873718},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16741546988487244}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2008.2006587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2008.2006587","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W194242946","https://openalex.org/W1534396055","https://openalex.org/W1638580935","https://openalex.org/W1967969088","https://openalex.org/W1975900269","https://openalex.org/W1985417024","https://openalex.org/W1995897300","https://openalex.org/W2038614136","https://openalex.org/W2043230024","https://openalex.org/W2045220410","https://openalex.org/W2045512849","https://openalex.org/W2062388999","https://openalex.org/W2063262040","https://openalex.org/W2067136705","https://openalex.org/W2071609006","https://openalex.org/W2090927030","https://openalex.org/W2103559027","https://openalex.org/W2113600901","https://openalex.org/W2125027820","https://openalex.org/W2135046866","https://openalex.org/W2136180695","https://openalex.org/W2138019504","https://openalex.org/W2142635246","https://openalex.org/W2146842127","https://openalex.org/W2149108880","https://openalex.org/W2156529323","https://openalex.org/W2156571999","https://openalex.org/W2157291679","https://openalex.org/W2158940042","https://openalex.org/W2161060033","https://openalex.org/W2162211921","https://openalex.org/W2165918462","https://openalex.org/W2167400582","https://openalex.org/W2167925415","https://openalex.org/W2168175751","https://openalex.org/W2169736182","https://openalex.org/W2503993098","https://openalex.org/W2615253071","https://openalex.org/W2802627035","https://openalex.org/W3099514962","https://openalex.org/W3142300713","https://openalex.org/W3145074154","https://openalex.org/W4214806317","https://openalex.org/W4242209908","https://openalex.org/W4255741480","https://openalex.org/W4289258898","https://openalex.org/W6632022301"],"related_works":["https://openalex.org/W2004468878","https://openalex.org/W1970377530","https://openalex.org/W2583208815","https://openalex.org/W4391019707","https://openalex.org/W2786015565","https://openalex.org/W3176148694","https://openalex.org/W1966715760","https://openalex.org/W1575232566","https://openalex.org/W1972437202","https://openalex.org/W2338217640"],"abstract_inverted_index":{"Principal":[0],"component":[1],"analysis":[2],"(PCA)":[3],"is":[4,34,64,133,152,174,200],"a":[5,52,67,121,136,144,156,185],"dimensionality":[6],"reduction":[7,69],"technique":[8],"used":[9],"in":[10,46,59,70],"most":[11],"fields":[12],"of":[13,23,56,73,81,97,114,146,188],"science":[14],"and":[15,100,139,148,206],"engineering.":[16],"It":[17,132],"aims":[18],"to":[19,41,65,143,161,202],"find":[20],"linear":[21],"combinations":[22],"the":[24,43,62,71,98,177],"input":[25],"variables":[26,108,165],"that":[27,35],"maximize":[28],"variance.":[29],"A":[30],"problem":[31],"with":[32],"PCA":[33,83,87,103,130],"it":[36],"typically":[37],"assigns":[38],"nonzero":[39],"loadings":[40,86,92],"all":[42,96],"variables,":[44],"which":[45,89,104,124],"high":[47],"dimensional":[48],"problems":[49],"can":[50],"require":[51],"very":[53,78],"large":[54],"number":[55,72],"coefficients.":[57,74],"But":[58],"many":[60],"applications,":[61],"aim":[63],"obtain":[66],"massive":[68],"There":[75],"are":[76],"two":[77],"different":[79],"types":[80],"sparse":[82,85,101,127],"problems:":[84],"(slPCA)":[88],"zeros":[90,105],"out":[91,106,163],"(while":[93],"generally":[94],"keeping":[95],"variables)":[99],"variable":[102,128],"whole":[107,164],"(typically":[109],"leaving":[110],"less":[111],"than":[112,167],"half":[113],"them).":[115],"In":[116],"this":[117,140],"paper,":[118],"we":[119,125,183],"propose":[120],"new":[122],"svPCA,":[123],"call":[126],"noisy":[129],"(svnPCA).":[131],"based":[134,153,175],"on":[135,154,176],"statistical":[137],"model,":[138],"gives":[141],"access":[142],"range":[145],"modeling":[147],"inferential":[149],"tools.":[150],"Estimation":[151],"optimizing":[155],"novel":[157,186],"penalized":[158],"log-likelihood":[159],"able":[160],"zero":[162],"rather":[166],"just":[168],"some":[169],"loadings.":[170],"The":[171,197],"estimation":[172],"algorithm":[173,199],"geodesic":[178],"steepest":[179],"descent":[180],"algorithm.":[181],"Finally,":[182],"develop":[184],"form":[187],"Bayesian":[189],"information":[190],"criterion":[191],"(BIC)":[192],"for":[193],"tuning":[194],"parameter":[195],"selection.":[196],"svnPCA":[198],"applied":[201],"both":[203],"simulated":[204],"data":[205],"real":[207],"functional":[208],"magnetic":[209],"resonance":[210],"imaging":[211],"(fMRI)":[212],"data.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":2}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
