{"id":"https://openalex.org/W4417284306","doi":"https://doi.org/10.1109/tfuzz.2025.3643471","title":"Low-Rank Matrix Factorization Induced Adaptive Divergent Graph Learning for Fuzzy Clustering","display_name":"Low-Rank Matrix Factorization Induced Adaptive Divergent Graph Learning for Fuzzy Clustering","publication_year":2025,"publication_date":"2025-12-12","ids":{"openalex":"https://openalex.org/W4417284306","doi":"https://doi.org/10.1109/tfuzz.2025.3643471"},"language":null,"primary_location":{"id":"doi:10.1109/tfuzz.2025.3643471","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2025.3643471","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","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":"Li Ma","orcid":"https://orcid.org/0009-0004-5487-2282"},"institutions":[{"id":"https://openalex.org/I24201400","display_name":"Chengdu University of Information Technology","ror":"https://ror.org/01yxwrh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I24201400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Ma","raw_affiliation_strings":["College of Applied Mathematics, Chengdu University of Information Technology, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0004-5487-2282","affiliations":[{"raw_affiliation_string":"College of Applied Mathematics, Chengdu University of Information Technology, Chengdu, China","institution_ids":["https://openalex.org/I24201400"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Nan Zhou","orcid":"https://orcid.org/0000-0002-0434-6231"},"institutions":[{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Zhou","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, China","School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, Sichuan, China"],"raw_orcid":"https://orcid.org/0000-0002-0434-6231","affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143"]},{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083428716","display_name":"Yuanhua Du","orcid":"https://orcid.org/0000-0002-9408-270X"},"institutions":[{"id":"https://openalex.org/I24201400","display_name":"Chengdu University of Information Technology","ror":"https://ror.org/01yxwrh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I24201400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanhua Du","raw_affiliation_strings":["College of Applied Mathematics, Chengdu University of Information Technology, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-9408-270X","affiliations":[{"raw_affiliation_string":"College of Applied Mathematics, Chengdu University of Information Technology, Chengdu, China","institution_ids":["https://openalex.org/I24201400"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenhao Wang","orcid":"https://orcid.org/0009-0000-0403-7220"},"institutions":[{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhao Wang","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, China","School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0000-0403-7220","affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143"]},{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013941056","display_name":"Kaibo Shi","orcid":"https://orcid.org/0000-0002-9863-9229"},"institutions":[{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaibo Shi","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, China","School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, Sichuan, China"],"raw_orcid":"https://orcid.org/0000-0002-9863-9229","affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143"]},{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I4210125143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083561828","display_name":"Witold Pedrycz","orcid":null},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Witold Pedrycz","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0002-9335-9930","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":0.36819602,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":"3","first_page":"705","last_page":"718"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.7932999730110168,"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":0.7932999730110168,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.09300000220537186,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.010200000368058681,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6470999717712402},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.4699999988079071},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.4691999852657318},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44130000472068787},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42829999327659607},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.42660000920295715},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4002000093460083},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.3831999897956848},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.3668000102043152}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6470999717712402},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5016999840736389},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5005999803543091},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.4699999988079071},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.4691999852657318},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44130000472068787},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42829999327659607},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.42660000920295715},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4002000093460083},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39070001244544983},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.3668000102043152},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3375000059604645},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.33719998598098755},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33649998903274536},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.3337000012397766},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.33169999718666077},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3310999870300293},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.30970001220703125},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.2985000014305115},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.28679999709129333},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C144817290","wikidata":"https://www.wikidata.org/wiki/Q2976575","display_name":"Biclustering","level":5,"score":0.25429999828338623},{"id":"https://openalex.org/C159246509","wikidata":"https://www.wikidata.org/wiki/Q5428725","display_name":"Factor graph","level":3,"score":0.2533999979496002},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2522999942302704},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2025.3643471","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2025.3643471","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1701760339","https://openalex.org/W1902027874","https://openalex.org/W1968154520","https://openalex.org/W1995450389","https://openalex.org/W2028302281","https://openalex.org/W2070670538","https://openalex.org/W2073835183","https://openalex.org/W2104819583","https://openalex.org/W2108119513","https://openalex.org/W2113713615","https://openalex.org/W2121947440","https://openalex.org/W2125531986","https://openalex.org/W2132914434","https://openalex.org/W2136635436","https://openalex.org/W2137823674","https://openalex.org/W2168103112","https://openalex.org/W2226862355","https://openalex.org/W2320933085","https://openalex.org/W2332282745","https://openalex.org/W2543728464","https://openalex.org/W2749408386","https://openalex.org/W2776766374","https://openalex.org/W2897197428","https://openalex.org/W2902688686","https://openalex.org/W3014603824","https://openalex.org/W3024853581","https://openalex.org/W3044063956","https://openalex.org/W3048323270","https://openalex.org/W3088893343","https://openalex.org/W3092472390","https://openalex.org/W3120086278","https://openalex.org/W3133771674","https://openalex.org/W3152660099","https://openalex.org/W3160787088","https://openalex.org/W3165494599","https://openalex.org/W3179460971","https://openalex.org/W4210889028","https://openalex.org/W4229080828","https://openalex.org/W4230367971","https://openalex.org/W4238805501","https://openalex.org/W4249667877","https://openalex.org/W4312336793","https://openalex.org/W4322201905","https://openalex.org/W4323664883","https://openalex.org/W4384130167","https://openalex.org/W4385489679","https://openalex.org/W4385783502","https://openalex.org/W4389987942","https://openalex.org/W4390787953","https://openalex.org/W4392611889","https://openalex.org/W4396690788","https://openalex.org/W4400315539","https://openalex.org/W4406200259","https://openalex.org/W4409919097","https://openalex.org/W4414229215"],"related_works":[],"abstract_inverted_index":{"This":[0,15],"paper":[1],"proposes":[2],"Low-rank":[3],"matrix":[4,23],"factorization":[5],"induced":[6],"Adaptive":[7],"divergent":[8],"Graph":[9],"learning":[10],"for":[11],"Fuzzy":[12],"Clustering":[13],"(LAGFC).":[14],"is":[16,109],"a":[17,61,87],"clustering":[18,30,135],"model":[19],"that":[20,44,130],"unifies":[21],"low-rank":[22],"factorization,":[24],"adaptive":[25,66],"graph":[26,46,67],"learning,":[27,68],"and":[28,36,48,104,115,146],"fuzzy":[29],"to":[31,111],"holistically":[32],"exploit":[33],"both":[34],"global":[35],"local":[37],"structural":[38],"information.":[39],"Unlike":[40],"conventional":[41],"graph-based":[42],"methods":[43,136],"decouple":[45],"construction":[47],"label":[49],"inference":[50],"into":[51],"separate":[52],"steps,":[53],"LAGFC":[54,131],"directly":[55],"generates":[56],"cluster":[57],"labels":[58],"by":[59],"incorporating":[60],"divergence":[62],"regularization":[63],"term":[64],"during":[65],"enabling":[69],"end-to-end":[70],"optimization.":[71],"To":[72],"enhance":[73],"robustness":[74],"against":[75],"noisy":[76],"data,":[77],"the":[78,82,113],"proposed":[79],"method":[80],"adopts":[81],"Maximum":[83],"Correntropy":[84],"Criterion":[85],"as":[86],"distance":[88],"metric,":[89],"effectively":[90],"suppressing":[91],"outlier":[92],"influence.":[93],"An":[94],"efficient":[95],"iterative":[96],"optimization":[97],"algorithm,":[98],"grounded":[99],"in":[100,140],"Fenchel":[101],"conjugate":[102],"theory":[103],"block":[105],"coordinate":[106],"update":[107],"techniques,":[108],"developed":[110],"solve":[112],"model,":[114],"theoretical":[116],"guarantees":[117],"of":[118],"convergence":[119],"are":[120],"provided.":[121],"Comprehensive":[122],"experiments":[123],"on":[124],"seven":[125],"real-world":[126],"image":[127],"datasets":[128],"demonstrate":[129],"outperforms":[132],"twelve":[133],"state-of-the-art":[134],"across":[137],"diverse":[138],"scenarios":[139],"most":[141],"cases,":[142],"validating":[143],"its":[144],"accuracy":[145],"robustness.":[147]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-12-12T00:00:00"}