{"id":"https://openalex.org/W4401728098","doi":"https://doi.org/10.1109/tpami.2024.3446537","title":"Tensorized and Compressed Multi-View Subspace Clustering via Structured Constraint","display_name":"Tensorized and Compressed Multi-View Subspace Clustering via Structured Constraint","publication_year":2024,"publication_date":"2024-08-20","ids":{"openalex":"https://openalex.org/W4401728098","doi":"https://doi.org/10.1109/tpami.2024.3446537","pmid":"https://pubmed.ncbi.nlm.nih.gov/39163175"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2024.3446537","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3446537","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101979335","display_name":"Wei Chang","orcid":"https://orcid.org/0000-0001-6286-5462"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Chang","raw_affiliation_strings":["School of Computer Science and School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100356341","display_name":"Huimin Chen","orcid":"https://orcid.org/0000-0002-7968-4948"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huimin Chen","raw_affiliation_strings":["School of Computer Science and School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003222421","display_name":"Feiping Nie","orcid":"https://orcid.org/0000-0002-0871-6519"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feiping Nie","raw_affiliation_strings":["School of Computer Science and School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030351224","display_name":"Rong Wang","orcid":"https://orcid.org/0000-0001-9240-6726"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Wang","raw_affiliation_strings":["School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106943753","display_name":"Xuelong Li","orcid":"https://orcid.org/0000-0003-2924-946X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelong Li","raw_affiliation_strings":["School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101979335"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":3.9886,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.94921474,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"46","issue":"12","first_page":"10434","last_page":"10451"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9944000244140625,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9944000244140625,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9693999886512756,"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/T12676","display_name":"Machine Learning and ELM","score":0.9642000198364258,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6677562594413757},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.604385495185852},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5573651194572449},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4645044505596161},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.45921680331230164},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4565202593803406},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4543243944644928},{"id":"https://openalex.org/keywords/local-consistency","display_name":"Local consistency","score":0.44281038641929626},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4416753649711609},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42580854892730713},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3756534457206726},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37301385402679443},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35259026288986206},{"id":"https://openalex.org/keywords/constraint-satisfaction-problem","display_name":"Constraint satisfaction problem","score":0.2982999086380005},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22255045175552368},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.18360108137130737}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6677562594413757},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.604385495185852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5573651194572449},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4645044505596161},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.45921680331230164},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4565202593803406},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4543243944644928},{"id":"https://openalex.org/C137105694","wikidata":"https://www.wikidata.org/wiki/Q3407510","display_name":"Local consistency","level":4,"score":0.44281038641929626},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4416753649711609},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42580854892730713},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3756534457206726},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37301385402679443},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35259026288986206},{"id":"https://openalex.org/C199622910","wikidata":"https://www.wikidata.org/wiki/Q1128326","display_name":"Constraint satisfaction problem","level":3,"score":0.2982999086380005},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22255045175552368},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.18360108137130737},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2024.3446537","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3446537","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:39163175","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39163175","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7365858389","display_name":null,"funder_award_id":"62176212","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1599555836","https://openalex.org/W1907775068","https://openalex.org/W1975172027","https://openalex.org/W1993962865","https://openalex.org/W2003361735","https://openalex.org/W2006533296","https://openalex.org/W2007339694","https://openalex.org/W2089468765","https://openalex.org/W2100075055","https://openalex.org/W2103560185","https://openalex.org/W2111854674","https://openalex.org/W2132914434","https://openalex.org/W2133576408","https://openalex.org/W2134529554","https://openalex.org/W2142109962","https://openalex.org/W2145152441","https://openalex.org/W2146610201","https://openalex.org/W2155904486","https://openalex.org/W2177347332","https://openalex.org/W2199534117","https://openalex.org/W2604983939","https://openalex.org/W2758611985","https://openalex.org/W2914429466","https://openalex.org/W2939666302","https://openalex.org/W2963165461","https://openalex.org/W2963840432","https://openalex.org/W2964378376","https://openalex.org/W2972882412","https://openalex.org/W2988613494","https://openalex.org/W2995931523","https://openalex.org/W2997739739","https://openalex.org/W3019954098","https://openalex.org/W3024343454","https://openalex.org/W3044063956","https://openalex.org/W3089195948","https://openalex.org/W3098561772","https://openalex.org/W3130503331","https://openalex.org/W3149863265","https://openalex.org/W3179442710","https://openalex.org/W3196973577","https://openalex.org/W3207496032","https://openalex.org/W4200226646","https://openalex.org/W4214544745","https://openalex.org/W4283827931","https://openalex.org/W4290927762","https://openalex.org/W4292263874","https://openalex.org/W4297322797","https://openalex.org/W4361984358","https://openalex.org/W4388919401","https://openalex.org/W6603183647","https://openalex.org/W6725836693","https://openalex.org/W6731661740","https://openalex.org/W6731871752","https://openalex.org/W6743484365","https://openalex.org/W6929385289"],"related_works":["https://openalex.org/W1533933130","https://openalex.org/W1980381208","https://openalex.org/W2364594919","https://openalex.org/W2167092671","https://openalex.org/W1522668611","https://openalex.org/W1861706286","https://openalex.org/W2219338811","https://openalex.org/W4299537742","https://openalex.org/W1995723671","https://openalex.org/W2164647769"],"abstract_inverted_index":{"Multi-view":[0],"learning":[1,64,77],"has":[2,150],"raised":[3],"more":[4,6],"and":[5,52,75,105,114,127,153,175,182],"attention":[7],"in":[8,39],"recent":[9],"years.":[10],"However,":[11],"traditional":[12],"approaches":[13],"only":[14],"focus":[15],"on":[16,124,173],"the":[17,21,31,40,46,72,88,99,112,135,141,144,147,155,158,180,189],"difference":[18,115],"while":[19],"ignoring":[20],"consistency":[22,113],"among":[23,116],"views.":[24],"It":[25],"may":[26],"make":[27],"some":[28],"views,":[29,117],"with":[30,191],"situation":[32],"of":[33,42,101,143,184],"data":[34],"abnormality":[35],"or":[36,193],"noise,":[37],"ineffective":[38],"progress":[41,74],"view":[43],"learning.":[44],"Besides,":[45],"current":[47],"datasets":[48,178],"have":[49],"become":[50],"high-dimensional":[51],"large-scale":[53],"gradually.":[54],"Therefore,":[55],"this":[56,166],"paper":[57],"proposes":[58],"a":[59,79,93,120],"novel":[60],"multi-view":[61,76],"compressed":[62],"subspace":[63],"method":[65],"via":[66],"low-rank":[67,121],"tensor":[68,122],"constraint,":[69,157],"which":[70,96],"incorporates":[71],"clustering":[73,159],"into":[78],"unified":[80],"framework.":[81],"First,":[82],"for":[83,188],"each":[84],"view,":[85],"we":[86,118],"take":[87],"partial":[89],"samples":[90],"to":[91,110,133,140],"build":[92],"small-size":[94],"dictionary,":[95],"can":[97,161],"reduce":[98],"effect":[100],"both":[102],"redundancy":[103],"information":[104],"computation":[106],"cost":[107],"greatly.":[108],"Then,":[109],"find":[111],"impose":[119],"constraint":[123],"these":[125],"representations":[126],"further":[128],"design":[129],"an":[130],"auto-weighted":[131],"mechanism":[132],"learn":[134],"optimal":[136],"representation.":[137],"Last,":[138],"due":[139],"non-square":[142],"learned":[145],"representation,":[146],"bipartite":[148],"graph":[149,167],"been":[151],"introduced,":[152],"under":[154],"structured":[156],"results":[160],"be":[162],"obtained":[163],"directly":[164],"from":[165],"without":[168],"any":[169],"post-processing.":[170],"Extensive":[171],"experiments":[172],"synthetic":[174],"real-world":[176],"benchmark":[177],"demonstrate":[179],"efficacy":[181],"efficiency":[183],"our":[185],"method,":[186],"especially":[187],"views":[190],"noise":[192],"outliers.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
