{"id":"https://openalex.org/W3013890231","doi":"https://doi.org/10.1109/tsp.2021.3061218","title":"Generalized Canonical Correlation Analysis: A Subspace Intersection Approach","display_name":"Generalized Canonical Correlation Analysis: A Subspace Intersection Approach","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3013890231","doi":"https://doi.org/10.1109/tsp.2021.3061218","mag":"3013890231"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2021.3061218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2021.3061218","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2003.11205","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079087496","display_name":"Mikael S\u00f8rensen","orcid":"https://orcid.org/0000-0003-4337-7417"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mikael Sorensen","raw_affiliation_strings":["Department of ECE, University of Virginia, Charlottesville, VA, USA"],"raw_orcid":"https://orcid.org/0000-0003-4337-7417","affiliations":[{"raw_affiliation_string":"Department of ECE, University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034936665","display_name":"Charilaos I. Kanatsoulis","orcid":"https://orcid.org/0000-0002-0952-1561"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charilaos I. Kanatsoulis","raw_affiliation_strings":["Department of ECE, University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":"https://orcid.org/0000-0002-0952-1561","affiliations":[{"raw_affiliation_string":"Department of ECE, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050186120","display_name":"Nicholas D. Sidiropoulos","orcid":"https://orcid.org/0000-0002-3385-7911"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas D. Sidiropoulos","raw_affiliation_strings":["Department of ECE, University of Virginia, Charlottesville, VA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3385-7911","affiliations":[{"raw_affiliation_string":"Department of ECE, University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1992,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.93267169,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"69","issue":null,"first_page":"2452","last_page":"2467"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9926000237464905,"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/T10057","display_name":"Face and Expression Recognition","score":0.9926000237464905,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9894000291824341,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9667999744415283,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/canonical-correlation","display_name":"Canonical correlation","score":0.8355972766876221},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7502875328063965},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.7180231809616089},{"id":"https://openalex.org/keywords/linear-algebra","display_name":"Linear algebra","score":0.5368386507034302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47561293840408325},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45906761288642883},{"id":"https://openalex.org/keywords/algebraic-number","display_name":"Algebraic number","score":0.4583749771118164},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.45830395817756653},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4522559642791748},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4517568349838257},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4398970305919647},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.438541442155838},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.4217367172241211},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4116279184818268},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4111427664756775},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4047337472438812},{"id":"https://openalex.org/keywords/algebra-over-a-field","display_name":"Algebra over a field","score":0.34454554319381714},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.326124906539917},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.09114637970924377}],"concepts":[{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.8355972766876221},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7502875328063965},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.7180231809616089},{"id":"https://openalex.org/C139352143","wikidata":"https://www.wikidata.org/wiki/Q82571","display_name":"Linear algebra","level":2,"score":0.5368386507034302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47561293840408325},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45906761288642883},{"id":"https://openalex.org/C9376300","wikidata":"https://www.wikidata.org/wiki/Q168817","display_name":"Algebraic number","level":2,"score":0.4583749771118164},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.45830395817756653},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4522559642791748},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4517568349838257},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4398970305919647},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.438541442155838},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.4217367172241211},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4116279184818268},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4111427664756775},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4047337472438812},{"id":"https://openalex.org/C136119220","wikidata":"https://www.wikidata.org/wiki/Q1000660","display_name":"Algebra over a field","level":2,"score":0.34454554319381714},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.326124906539917},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.09114637970924377},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2021.3061218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2021.3061218","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"},{"id":"pmh:oai:arXiv.org:2003.11205","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.11205","pdf_url":"https://arxiv.org/pdf/2003.11205","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2003.11205","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.11205","pdf_url":"https://arxiv.org/pdf/2003.11205","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1764534353","display_name":null,"funder_award_id":"NSF ECCS-1807660","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G179677298","display_name":null,"funder_award_id":"ECCS 1852831","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G8562589355","display_name":null,"funder_award_id":"ARO W911NF1910407","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"}],"funders":[{"id":"https://openalex.org/F4320335353","display_name":"National Science Foundation of Sri Lanka","ror":"https://ror.org/010xaa060"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W22168010","https://openalex.org/W131753375","https://openalex.org/W310972808","https://openalex.org/W355000591","https://openalex.org/W563157365","https://openalex.org/W1523385540","https://openalex.org/W1532325895","https://openalex.org/W1601553748","https://openalex.org/W1664345024","https://openalex.org/W1882496656","https://openalex.org/W1967827763","https://openalex.org/W1975077471","https://openalex.org/W1984953230","https://openalex.org/W1993570538","https://openalex.org/W2001600470","https://openalex.org/W2008248260","https://openalex.org/W2008929650","https://openalex.org/W2024181699","https://openalex.org/W2025341678","https://openalex.org/W2070996757","https://openalex.org/W2081689238","https://openalex.org/W2082930519","https://openalex.org/W2085406278","https://openalex.org/W2098841537","https://openalex.org/W2100235303","https://openalex.org/W2108502868","https://openalex.org/W2110533019","https://openalex.org/W2118090838","https://openalex.org/W2125290066","https://openalex.org/W2125972593","https://openalex.org/W2126706529","https://openalex.org/W2129625650","https://openalex.org/W2131436045","https://openalex.org/W2136671499","https://openalex.org/W2154202969","https://openalex.org/W2288743170","https://openalex.org/W2337541833","https://openalex.org/W2582733512","https://openalex.org/W2583191533","https://openalex.org/W2767589925","https://openalex.org/W2799107559","https://openalex.org/W2950516383","https://openalex.org/W2963055343","https://openalex.org/W2970533962","https://openalex.org/W2978214371","https://openalex.org/W3013975998","https://openalex.org/W3123006928","https://openalex.org/W3214122883","https://openalex.org/W4213009331","https://openalex.org/W4230046490","https://openalex.org/W4237951138","https://openalex.org/W4253938478","https://openalex.org/W6600880057","https://openalex.org/W6610929883","https://openalex.org/W6631216910","https://openalex.org/W6636069787","https://openalex.org/W6674632333","https://openalex.org/W6677518113","https://openalex.org/W6678658080","https://openalex.org/W6678813167","https://openalex.org/W6678885645","https://openalex.org/W6679376003","https://openalex.org/W6696197757","https://openalex.org/W6703432866"],"related_works":["https://openalex.org/W2026584557","https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W4238433571","https://openalex.org/W3174044702","https://openalex.org/W2967848559"],"abstract_inverted_index":{"Generalized":[0],"Canonical":[1],"Correlation":[2],"Analysis":[3],"(GCCA)":[4],"is":[5,92,103,119,127],"an":[6],"important":[7],"tool":[8],"that":[9,28,86,94],"finds":[10],"numerous":[11],"applications":[12],"in":[13],"data":[14,146],"mining,":[15],"machine":[16],"learning,":[17],"and":[18,44,56,108],"artificial":[19],"intelligence.":[20],"It":[21,91],"aims":[22],"at":[23],"finding":[24],"\u2018common\u2019":[25],"random":[26],"variables":[27],"are":[29,121,148],"strongly":[30],"correlated":[31],"across":[32],"multiple":[33],"feature":[34],"representations":[35],"(views)":[36],"of":[37,41,59,68,100,115,154],"the":[38,54,66,112,116,152,155],"same":[39],"set":[40],"entities.":[42],"CCA":[43],"to":[45,105,136,150],"a":[46,74,82,96],"lesser":[47],"extent":[48],"GCCA":[49,79,102,125,139],"have":[50],"been":[51],"studied":[52],"from":[53,65,95],"statistical":[55],"algorithmic":[57],"points":[58],"view,":[60,101],"but":[61],"not":[62],"as":[63,142,144],"much":[64],"standpoint":[67],"linear":[69,97],"algebra.":[70],"This":[71],"paper":[72],"offers":[73],"fresh":[75],"algebraic":[76],"perspective":[77],"on":[78,81,130],"based":[80,129],"(bi-)linear":[83],"generative":[84],"model":[85],"naturally":[87],"captures":[88],"its":[89],"essence.":[90],"shown":[93],"algebra":[98],"point":[99],"tantamount":[104],"subspace":[106,114,131],"intersection;":[107],"conditions":[109],"under":[110],"which":[111,133],"common":[113],"different":[117],"views":[118],"identifiable":[120],"provided.":[122],"A":[123],"novel":[124],"algorithm":[126],"proposed":[128,156],"intersection,":[132],"scales":[134],"up":[135],"handle":[137],"large":[138],"tasks.":[140],"Synthetic":[141],"well":[143],"real":[145],"experiments":[147],"provided":[149],"showcase":[151],"effectiveness":[153],"approach.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2020-04-03T00:00:00"}