{"id":"https://openalex.org/W4416748756","doi":"https://doi.org/10.1109/tetci.2025.3634722","title":"Tensorized Non-Negative Multi-Attribute Subspace Clustering","display_name":"Tensorized Non-Negative Multi-Attribute Subspace Clustering","publication_year":2025,"publication_date":"2025-11-27","ids":{"openalex":"https://openalex.org/W4416748756","doi":"https://doi.org/10.1109/tetci.2025.3634722"},"language":null,"primary_location":{"id":"doi:10.1109/tetci.2025.3634722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2025.3634722","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","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":null,"display_name":"Zixuan Lin","orcid":"https://orcid.org/0009-0003-7517-9690"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixuan Lin","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0003-7517-9690","affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090101808","display_name":"Guoxu Zhou","orcid":"https://orcid.org/0000-0003-1187-577X"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoxu Zhou","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1187-577X","affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090225684","display_name":"Haonan Huang","orcid":"https://orcid.org/0000-0001-7223-5202"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Haonan Huang","raw_affiliation_strings":["RIKEN AIP, Chuo-ku, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-7223-5202","affiliations":[{"raw_affiliation_string":"RIKEN AIP, Chuo-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015407738","display_name":"Zhenhao Huang","orcid":"https://orcid.org/0000-0001-5874-7148"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhao Huang","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5874-7148","affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070961417","display_name":"Yuning Qiu","orcid":"https://orcid.org/0000-0003-0268-0890"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuning Qiu","raw_affiliation_strings":["RIKEN AIP, Chuo-ku, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-0268-0890","affiliations":[{"raw_affiliation_string":"RIKEN AIP, Chuo-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083182987","display_name":"Qibin Zhao","orcid":"https://orcid.org/0000-0002-4442-3182"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qibin Zhao","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4442-3182","affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043262479","display_name":"Shengli Xie","orcid":"https://orcid.org/0000-0003-2041-5214"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengli Xie","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2041-5214","affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32532654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"2","first_page":"1157","last_page":"1169"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.40549999475479126,"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":0.40549999475479126,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.16509999334812164,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.10360000282526016,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7649999856948853},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.680400013923645},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5608000159263611},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5342000126838684},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5138000249862671},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42250001430511475},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4180999994277954},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4077000021934509},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.38100001215934753}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7649999856948853},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.680400013923645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6287000179290771},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5608000159263611},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5555999875068665},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5342000126838684},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5138000249862671},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42250001430511475},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4180999994277954},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4077000021934509},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40720000863075256},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.3750999867916107},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36340001225471497},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.3296999931335449},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.30880001187324524},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2962000072002411},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.29499998688697815},{"id":"https://openalex.org/C39235581","wikidata":"https://www.wikidata.org/wiki/Q5158434","display_name":"Conceptual clustering","level":5,"score":0.2939999997615814},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.2824999988079071},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.2646999955177307},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2025.3634722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2025.3634722","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1585854524","display_name":null,"funder_award_id":"62203124","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2961000088","display_name":null,"funder_award_id":"62406077","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G526035975","display_name":null,"funder_award_id":"2023A1515012916","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G8643937652","display_name":null,"funder_award_id":"2024A1515010114","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Subspace":[0,72],"clustering":[1,19,40,193],"has":[2],"been":[3],"successful":[4],"in":[5,12,34],"unsupervised":[6],"learning":[7,26,94],"by":[8,201],"revealing":[9],"low-dimensional":[10],"structures":[11],"high-dimensional":[13],"data.":[14,36,88,149],"However,":[15],"most":[16],"existing":[17],"subspace":[18,39],"methods":[20],"rely":[21],"on":[22,129,173,185],"a":[23,53,65,92,122,161,192,202],"single":[24],"self-expressive":[25],"process":[27],"and":[28,81,112],"neglect":[29],"the":[30,45,49,78,82,86,130,135,186,198],"multi-attribute":[31,83,93],"information":[32,84],"inherent":[33],"real-world":[35,175],"Moreover,":[37],"traditional":[38],"often":[41],"fails":[42],"to":[43,52,96,108,159],"capture":[44,109],"spatial":[46,79,118],"structure":[47,80],"of":[48,55,85,134,138,195,205],"data,":[50],"leading":[51],"loss":[54],"important":[56],"attribute":[57,169],"information.":[58,170],"To":[59,115],"address":[60],"these":[61],"issues,":[62],"we":[63,120],"propose":[64],"novel":[66],"approach":[67,143,200],"called":[68],"Tensorized":[69],"Non-negative":[70],"Multi-Attribute":[71],"Clustering":[73],"(TNMSC),":[74],"which":[75],"preserves":[76],"both":[77],"original":[87],"Specifically,":[89],"TNMSC":[90,151,179],"uses":[91],"framework":[95],"construct":[97],"separate":[98],"affinity":[99,164],"representations":[100],"for":[101,146],"each":[102],"attribute,":[103],"while":[104],"imposing":[105],"non-negativity":[106],"constraints":[107],"more":[110],"interpretable":[111],"richer":[113],"features.":[114],"further":[116],"retain":[117],"information,":[119],"introduce":[121],"tensor":[123],"decomposition-based":[124],"representation":[125,165],"that":[126,166,178],"directly":[127],"operates":[128],"high-order":[131],"(tensor)":[132],"form":[133],"data":[136],"instead":[137],"flattened":[139],"vectors,":[140],"making":[141],"our":[142,189],"particularly":[144],"advantageous":[145],"multidimensional":[147],"image":[148],"Finally,":[150],"explores":[152],"consistent":[153],"topological":[154],"correlation":[155],"across":[156],"different":[157],"attributes":[158],"learn":[160],"refined":[162],"consensus":[163],"integrates":[167],"all":[168],"Extensive":[171],"experiments":[172],"seven":[174],"datasets":[176],"demonstrate":[177],"outperforms":[180],"state-of-the-art":[181],"methods.":[182],"For":[183],"instance,":[184],"COIL20":[187],"dataset,":[188],"method":[190],"achieves":[191],"accuracy":[194],"83.71%,":[196],"surpassing":[197],"second-best":[199],"significant":[203],"margin":[204],"5.86%.":[206]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-28T00:00:00"}