{"id":"https://openalex.org/W3163644211","doi":"https://doi.org/10.1109/tbdata.2021.3079234","title":"Deep Tensor CCA for Multi-view Learning","display_name":"Deep Tensor CCA for Multi-view Learning","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3163644211","doi":"https://doi.org/10.1109/tbdata.2021.3079234","mag":"3163644211"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2021.3079234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2021.3079234","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Big Data","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/A5083863808","display_name":"Hok Shing Wong","orcid":"https://orcid.org/0009-0004-7267-778X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hok Shing Wong","raw_affiliation_strings":["Mathematics, The Chinese University of Hong Kong, 26451 Hong Kong, Hong Kong, Hong Kong, (e-mail: hswong@math.cuhk.edu.hk)","[Mathematics, The Chinese University of Hong Kong, 26451 Hong Kong, Hong Kong, Hong Kong, (e-mail: hswong@math.cuhk.edu.hk)]"],"affiliations":[{"raw_affiliation_string":"Mathematics, The Chinese University of Hong Kong, 26451 Hong Kong, Hong Kong, Hong Kong, (e-mail: hswong@math.cuhk.edu.hk)","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"[Mathematics, The Chinese University of Hong Kong, 26451 Hong Kong, Hong Kong, Hong Kong, (e-mail: hswong@math.cuhk.edu.hk)]","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100336208","display_name":"Li Wang","orcid":"https://orcid.org/0000-0003-2658-4262"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li Wang","raw_affiliation_strings":["Mathematics and Computer Science and Engineering, The University of Texas at Arlington, 12329 Arlington, Texas, United States, (e-mail: li.wang@uta.edu)","[Mathematics and Computer Science and Engineering, The University of Texas at Arlington, 12329 Arlington, Texas, United States, (e-mail: li.wang@uta.edu)]"],"affiliations":[{"raw_affiliation_string":"Mathematics and Computer Science and Engineering, The University of Texas at Arlington, 12329 Arlington, Texas, United States, (e-mail: li.wang@uta.edu)","institution_ids":["https://openalex.org/I189196454"]},{"raw_affiliation_string":"[Mathematics and Computer Science and Engineering, The University of Texas at Arlington, 12329 Arlington, Texas, United States, (e-mail: li.wang@uta.edu)]","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004126693","display_name":"Raymond H. Chan","orcid":"https://orcid.org/0000-0003-0910-4685"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Raymond Chan","raw_affiliation_strings":["Mathematics, City University of Hong Kong, 53025 Kowloon, Hong Kong, Hong Kong, (e-mail: rchan.sci@cityu.edu.hk)","[Mathematics, City University of Hong Kong, 53025 Kowloon, Hong Kong, Hong Kong, (e-mail: rchan.sci@cityu.edu.hk)]"],"affiliations":[{"raw_affiliation_string":"Mathematics, City University of Hong Kong, 53025 Kowloon, Hong Kong, Hong Kong, (e-mail: rchan.sci@cityu.edu.hk)","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"[Mathematics, City University of Hong Kong, 53025 Kowloon, Hong Kong, Hong Kong, (e-mail: rchan.sci@cityu.edu.hk)]","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059443966","display_name":"Tieyong Zeng","orcid":"https://orcid.org/0000-0002-0688-202X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tieyong Zeng","raw_affiliation_strings":["Mathematics, the Chinese University of Hong Kong, HongKong, Hongkong, Hong Kong, (e-mail: zeng@math.cuhk.edu.hk)","[Mathematics, the Chinese University of Hong Kong, HongKong, Hongkong, Hong Kong, (e-mail: zeng@math.cuhk.edu.hk)]"],"affiliations":[{"raw_affiliation_string":"Mathematics, the Chinese University of Hong Kong, HongKong, Hongkong, Hong Kong, (e-mail: zeng@math.cuhk.edu.hk)","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"[Mathematics, the Chinese University of Hong Kong, HongKong, Hongkong, Hong Kong, (e-mail: zeng@math.cuhk.edu.hk)]","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5083863808"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":2.1461,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.88029021,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9639999866485596,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9545999765396118,"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/computer-science","display_name":"Computer science","score":0.7685604095458984},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.7604062557220459},{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.6958632469177246},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6132922172546387},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.563330352306366},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.557489812374115},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.5242422223091125},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.48211669921875},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4524489939212799},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4222198724746704},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4203488528728485},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3619266450405121},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3595121502876282},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3426961302757263},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15337693691253662},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.09535238146781921}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7685604095458984},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.7604062557220459},{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.6958632469177246},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6132922172546387},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.563330352306366},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.557489812374115},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.5242422223091125},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.48211669921875},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4524489939212799},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4222198724746704},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4203488528728485},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3619266450405121},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3595121502876282},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3426961302757263},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15337693691253662},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.09535238146781921},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/tbdata.2021.3079234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2021.3079234","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3578602991","display_name":null,"funder_award_id":"11671002","funder_id":"https://openalex.org/F4320329293","funder_display_name":"Data Center of Management Science, National Natural Science Foundation of China - Peking University"}],"funders":[{"id":"https://openalex.org/F4320329293","display_name":"Data Center of Management Science, National Natural Science Foundation of China - Peking University","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W1523385540","https://openalex.org/W1566135517","https://openalex.org/W1670132599","https://openalex.org/W1672347394","https://openalex.org/W1883346539","https://openalex.org/W1959608418","https://openalex.org/W1991042426","https://openalex.org/W2000215628","https://openalex.org/W2001600470","https://openalex.org/W2007972815","https://openalex.org/W2013912476","https://openalex.org/W2023925753","https://openalex.org/W2025341678","https://openalex.org/W2025603201","https://openalex.org/W2047631354","https://openalex.org/W2048679005","https://openalex.org/W2096663965","https://openalex.org/W2100235303","https://openalex.org/W2100495367","https://openalex.org/W2106277773","https://openalex.org/W2107034620","https://openalex.org/W2109743529","https://openalex.org/W2125290066","https://openalex.org/W2153635508","https://openalex.org/W2154624311","https://openalex.org/W2159184562","https://openalex.org/W2162915993","https://openalex.org/W2163352848","https://openalex.org/W2166049352","https://openalex.org/W2202025056","https://openalex.org/W2274787793","https://openalex.org/W2400826247","https://openalex.org/W2405732242","https://openalex.org/W2414522539","https://openalex.org/W2530846021","https://openalex.org/W2544822491","https://openalex.org/W2590019597","https://openalex.org/W2730405534","https://openalex.org/W2767589925","https://openalex.org/W2806658157","https://openalex.org/W2886204470","https://openalex.org/W2926388138","https://openalex.org/W2931956500","https://openalex.org/W2949579163","https://openalex.org/W2970948008","https://openalex.org/W2972630054","https://openalex.org/W2987170822","https://openalex.org/W3007380221","https://openalex.org/W3014067266","https://openalex.org/W3120740533","https://openalex.org/W3144619878","https://openalex.org/W3149375329","https://openalex.org/W4237951138","https://openalex.org/W4295312788","https://openalex.org/W6631216910","https://openalex.org/W6636883489","https://openalex.org/W6639103823","https://openalex.org/W6640963894","https://openalex.org/W6678885645","https://openalex.org/W6683233156","https://openalex.org/W6694398804","https://openalex.org/W6713704110","https://openalex.org/W6728094556","https://openalex.org/W6729203000","https://openalex.org/W6761244968","https://openalex.org/W6766978945","https://openalex.org/W6793156980"],"related_works":["https://openalex.org/W2315242963","https://openalex.org/W2444009674","https://openalex.org/W4379256054","https://openalex.org/W2093953080","https://openalex.org/W47805180","https://openalex.org/W2963838862","https://openalex.org/W3015641590","https://openalex.org/W3216281372","https://openalex.org/W2987657992","https://openalex.org/W2949531434"],"abstract_inverted_index":{"We":[0],"present":[1],"Deep":[2],"Tensor":[3],"Canonical":[4],"Correlation":[5],"Analysis":[6],"(DTCCA),":[7],"a":[8,101,148,165],"method":[9],"to":[10,132],"learn":[11],"complex":[12],"nonlinear":[13,102,178],"transformations":[14,61],"of":[15,21,37,60,62,86,104,123,140,157,168,190],"multiple":[16,39],"views":[17,40],"(more":[18],"than":[19],"two)":[20],"data":[22,136,143,163,185],"such":[23],"that":[24],"the":[25,56,70,76,83,124,134,154,188,191],"resulting":[26,77],"representations":[27,139],"are":[28,65],"linearly":[29],"correlated":[30],"in":[31],"high":[32],"order.":[33],"The":[34],"high-order":[35,71],"correlation":[36],"given":[38,142],"is":[41,47,100],"modeled":[42],"by":[43,68,94],"covariance":[44],"tensor,":[45],"which":[46,89],"different":[48],"from":[49],"most":[50],"CCA":[51,106],"formulations":[52],"relying":[53],"solely":[54],"on":[55,182],"pairwise":[57],"correlations.":[58],"Parameters":[59],"each":[63],"view":[64],"jointly":[66],"learned":[67],"maximizing":[69],"canonical":[72],"correlation.":[73],"To":[74],"solve":[75],"problem,":[78],"we":[79],"reformulate":[80],"it":[81,171],"as":[82,147],"best":[84],"sum":[85],"rank-1":[87],"approximation,":[88],"can":[90,118,151],"be":[91],"efficiently":[92,152],"solved":[93],"existing":[95],"tensor":[96,105],"decomposition":[97],"method.":[98,193],"DTCCA":[99,115,146],"extension":[103],"(TCCA)":[107],"via":[108],"deep":[109],"networks.":[110],"Comparing":[111],"with":[112,120],"kernel":[113],"TCCA,":[114],"not":[116,130],"only":[117],"deal":[119],"arbitrary":[121],"dimensions":[122],"input":[125],"data,":[126],"but":[127],"also":[128,172],"does":[129],"need":[131],"maintain":[133],"training":[135],"for":[137,159,176],"computing":[138],"any":[141],"point.":[144],"Hence,":[145],"unified":[149],"model":[150],"overcome":[153],"scalable":[155],"issue":[156],"TCCA":[158,175],"either":[160],"high-dimensional":[161],"multi-view":[162,184],"or":[164],"large":[166],"amount":[167],"views,":[169],"and":[170],"naturally":[173],"extends":[174],"learning":[177],"representation.":[179],"Extensive":[180],"experiments":[181],"four":[183],"sets":[186],"demonstrate":[187],"effectiveness":[189],"proposed":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}