{"id":"https://openalex.org/W4411171623","doi":"https://doi.org/10.1109/tai.2025.3578585","title":"Toward Robust Nonlinear Subspace Clustering: A Kernel Learning Approach","display_name":"Toward Robust Nonlinear Subspace Clustering: A Kernel Learning Approach","publication_year":2025,"publication_date":"2025-06-10","ids":{"openalex":"https://openalex.org/W4411171623","doi":"https://doi.org/10.1109/tai.2025.3578585"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2025.3578585","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2025.3578585","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"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 Artificial 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":"Kunpeng Xu","orcid":"https://orcid.org/0000-0002-9349-4390"},"institutions":[{"id":"https://openalex.org/I135117807","display_name":"Universit\u00e9 de Sherbrooke","ror":"https://ror.org/00kybxq39","country_code":"CA","type":"education","lineage":["https://openalex.org/I135117807"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Kunpeng Xu","raw_affiliation_strings":["Department of Computer Science, Universit&#x00E9; de Sherbrooke, Sherbrooke, Quebec, Canada","Department of Computer Science, Universit&#x00E9; de Sherbrooke,, Sherbrooke, Quebec, Canada"],"raw_orcid":"https://orcid.org/0000-0002-9349-4390","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Universit&#x00E9; de Sherbrooke, Sherbrooke, Quebec, Canada","institution_ids":["https://openalex.org/I135117807"]},{"raw_affiliation_string":"Department of Computer Science, Universit&#x00E9; de Sherbrooke,, Sherbrooke, Quebec, Canada","institution_ids":["https://openalex.org/I135117807"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091369584","display_name":"Lifei Chen","orcid":"https://orcid.org/0000-0003-3568-8899"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lifei Chen","raw_affiliation_strings":["College of Computer and Cyber Security, Fujian Normal University, Fuzhou, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0003-3568-8899","affiliations":[{"raw_affiliation_string":"College of Computer and Cyber Security, Fujian Normal University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065104101","display_name":"Shengrui Wang","orcid":"https://orcid.org/0000-0001-6863-7022"},"institutions":[{"id":"https://openalex.org/I135117807","display_name":"Universit\u00e9 de Sherbrooke","ror":"https://ror.org/00kybxq39","country_code":"CA","type":"education","lineage":["https://openalex.org/I135117807"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Shengrui Wang","raw_affiliation_strings":["Department of Computer Science, Universit&#x00E9; de Sherbrooke, Sherbrooke, Quebec, Canada","Department of Computer Science, Universit&#x00E9; de Sherbrooke,, Sherbrooke, Quebec, Canada"],"raw_orcid":"https://orcid.org/0000-0001-6863-7022","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Universit&#x00E9; de Sherbrooke, Sherbrooke, Quebec, Canada","institution_ids":["https://openalex.org/I135117807"]},{"raw_affiliation_string":"Department of Computer Science, Universit&#x00E9; de Sherbrooke,, Sherbrooke, Quebec, Canada","institution_ids":["https://openalex.org/I135117807"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.1242,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.96691438,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"7","issue":"2","first_page":"726","last_page":"739"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9595000147819519,"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":0.9595000147819519,"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":0.9437999725341797,"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/kernel","display_name":"Kernel (algebra)","score":0.6145035624504089},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6128125786781311},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5429264903068542},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5172575116157532},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5036212801933289},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4909367859363556},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.4840490221977234},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4135611057281494},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40514901280403137},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.16812020540237427},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12028977274894714},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07006925344467163}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6145035624504089},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6128125786781311},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5429264903068542},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5172575116157532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5036212801933289},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4909367859363556},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.4840490221977234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4135611057281494},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40514901280403137},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.16812020540237427},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12028977274894714},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07006925344467163},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2025.3578585","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2025.3578585","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"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 Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3327627158","display_name":null,"funder_award_id":"U1805263","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4164313007","display_name":null,"funder_award_id":"2024J01067","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1600471557","https://openalex.org/W1979089718","https://openalex.org/W1986007546","https://openalex.org/W1993962865","https://openalex.org/W1997201895","https://openalex.org/W1998627394","https://openalex.org/W2017441234","https://openalex.org/W2043360443","https://openalex.org/W2118858274","https://openalex.org/W2132914434","https://openalex.org/W2132967688","https://openalex.org/W2148894497","https://openalex.org/W2151155403","https://openalex.org/W2177347332","https://openalex.org/W2410894298","https://openalex.org/W2883604340","https://openalex.org/W2893652381","https://openalex.org/W2897582990","https://openalex.org/W2898233200","https://openalex.org/W2942755646","https://openalex.org/W2947617682","https://openalex.org/W2963089385","https://openalex.org/W2963165461","https://openalex.org/W2963764968","https://openalex.org/W2982941363","https://openalex.org/W2996588988","https://openalex.org/W3025752507","https://openalex.org/W4213082874","https://openalex.org/W4299145603","https://openalex.org/W4313427311","https://openalex.org/W4319779660","https://openalex.org/W4323338655","https://openalex.org/W4382239329","https://openalex.org/W4384023731","https://openalex.org/W4385232475","https://openalex.org/W4387409035","https://openalex.org/W4391469850","https://openalex.org/W4391513848","https://openalex.org/W4400726743","https://openalex.org/W4402544754","https://openalex.org/W4403147589","https://openalex.org/W4406794479","https://openalex.org/W4409361287"],"related_works":["https://openalex.org/W2089892314","https://openalex.org/W1603091392","https://openalex.org/W4386075310","https://openalex.org/W2095626363","https://openalex.org/W2169565408","https://openalex.org/W2127229869","https://openalex.org/W3123056048","https://openalex.org/W2129978300","https://openalex.org/W2150638158","https://openalex.org/W2121506664"],"abstract_inverted_index":{"Kernel-based":[0],"subspace":[1,84],"clustering,":[2],"which":[3,110],"addresses":[4],"the":[5,28,37,41,46,50,56,62,94,97,105,112,115,125,137,166,169],"nonlinear":[6,47,83,133],"structures":[7,44],"in":[8,45,131],"data,":[9],"is":[10],"an":[11,140],"evolving":[12],"area":[13],"of":[14,30,39,52,61,114,129,139,149,168],"research.":[15],"Despite":[16],"noteworthy":[17],"progressions,":[18],"prevailing":[19],"methodologies":[20],"predominantly":[21],"grapple":[22],"with":[23,154],"limitations":[24],"relating":[25],"to":[26],"(i)":[27],"influence":[29],"predefined":[31],"kernels":[32],"on":[33,55,160],"model":[34],"performance;":[35],"(ii)":[36],"difficulty":[38],"preserving":[40],"original":[42],"manifold":[43,127],"space;":[48],"(iii)":[49],"dependency":[51],"spectral-type":[53],"strategies":[54],"ideal":[57],"block":[58],"diagonal":[59],"structure":[60,128],"affinity":[63,143],"matrix.":[64,144],"To":[65],"address":[66],"these":[67],"limitations,":[68],"this":[69,120],"paper":[70],"presents":[71],"a":[72,78,88,132],"Data-driven":[73],"Kernel":[74],"Learning":[75],"Model":[76],"(DKLM),":[77],"novel":[79],"paradigm":[80],"for":[81],"kernel-induced":[82],"clustering.":[85],"DKLM":[86,123,150],"provides":[87],"data-driven":[89],"approach":[90],"that":[91],"directly":[92],"learns":[93],"kernel":[95],"from":[96],"data\u2019s":[98],"self-representation,":[99],"ensuring":[100],"adaptive":[101],"weighting":[102],"and":[103,162],"satisfying":[104],"multiplicative":[106],"triangle":[107],"inequality":[108],"constraint,":[109],"enhances":[111],"robustness":[113],"learned":[116,121],"kernel.":[117],"By":[118],"leveraging":[119],"kernel,":[122],"preserves":[124],"local":[126],"data":[130],"space":[134],"while":[135],"promoting":[136],"formation":[138],"optimal":[141],"block-diagonal":[142],"A":[145],"thorough":[146],"theoretical":[147],"examination":[148],"reveals":[151],"its":[152],"relationship":[153],"existing":[155],"clustering":[156],"paradigms.":[157],"Comprehensive":[158],"experiments":[159],"synthetic":[161],"real-world":[163],"datasets":[164],"demonstrate":[165],"effectiveness":[167],"proposed":[170],"method.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5}],"updated_date":"2026-02-04T23:10:29.248076","created_date":"2025-10-10T00:00:00"}
