{"id":"https://openalex.org/W7124940873","doi":"https://doi.org/10.1109/tpami.2026.3655456","title":"Scalable Semi-Supervised Learning With Discriminative Label Propagation and Correction","display_name":"Scalable Semi-Supervised Learning With Discriminative Label Propagation and Correction","publication_year":2026,"publication_date":"2026-01-19","ids":{"openalex":"https://openalex.org/W7124940873","doi":"https://doi.org/10.1109/tpami.2026.3655456","pmid":"https://pubmed.ncbi.nlm.nih.gov/41553898"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2026.3655456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3655456","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":true,"oa_status":"green","oa_url":"https://orcid.org/0009-0006-3153-6125","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123396512","display_name":"Bingbing Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingbing Jiang","raw_affiliation_strings":["Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0006-3153-6125","affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123416000","display_name":"Jie Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wen","raw_affiliation_strings":["Shenzhen Key Laboratory of Visual Object Detection and Recognition, Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-9554-2379","affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Visual Object Detection and Recognition, Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123370357","display_name":"Zidong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I124357947","display_name":"University of London","ror":"https://ror.org/04cw6st05","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947"]},{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zidong Wang","raw_affiliation_strings":["Department of Computer Science, Brunel University of London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0002-9576-7401","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Brunel University of London, London, U.K","institution_ids":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122435402","display_name":"Weiguo Sheng","orcid":null},"institutions":[{"id":"https://openalex.org/I163151501","display_name":"Hangzhou Normal University","ror":"https://ror.org/014v1mr15","country_code":"CN","type":"education","lineage":["https://openalex.org/I163151501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiguo Sheng","raw_affiliation_strings":["School of Information Science and Technology, Hangzhou Normal University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9680-5126","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Hangzhou Normal University, Hangzhou, China","institution_ids":["https://openalex.org/I163151501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123370944","display_name":"Zhiwen Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwen Yu","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0935-5890","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123444271","display_name":"Huanhuan Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanhuan Chen","raw_affiliation_strings":["School of Computer Science and Technology, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-3918-384X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123444019","display_name":"Weiping Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I199305430","display_name":"Nantong University","ror":"https://ror.org/02afcvw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I199305430"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiping Ding","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Nantong University, Nantong, China"],"raw_orcid":"https://orcid.org/0000-0002-3180-7347","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Nantong University, Nantong, China","institution_ids":["https://openalex.org/I199305430"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":14.5419,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.98047386,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"48","issue":"6","first_page":"6156","last_page":"6173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.5963000059127808,"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":0.5963000059127808,"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":0.11980000138282776,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.05620000138878822,"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/discriminative-model","display_name":"Discriminative model","score":0.8012999892234802},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7297999858856201},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6309999823570251},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5570999979972839},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5299000144004822},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4431999921798706},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.42890000343322754},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4250999987125397},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42309999465942383},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41780000925064087}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8012999892234802},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7297999858856201},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6601999998092651},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6309999823570251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6220999956130981},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5570999979972839},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5490999817848206},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5299000144004822},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4431999921798706},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.42890000343322754},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4250999987125397},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42309999465942383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41780000925064087},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.36309999227523804},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.34310001134872437},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33629998564720154},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tpami.2026.3655456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3655456","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:41553898","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41553898","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},{"id":"pmh:oai:bura.brunel.ac.uk:2438/33043","is_oa":true,"landing_page_url":"https://orcid.org/0009-0006-3153-6125","pdf_url":null,"source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:bura.brunel.ac.uk:2438/33043","is_oa":true,"landing_page_url":"https://orcid.org/0009-0006-3153-6125","pdf_url":null,"source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"score":0.795467734336853,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1242006901","display_name":null,"funder_award_id":"62576128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1581597255","display_name":null,"funder_award_id":"62576178","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3386551668","display_name":null,"funder_award_id":"92467109","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4286351655","display_name":null,"funder_award_id":"U2433216","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5031074842","display_name":null,"funder_award_id":"62572199","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5618573370","display_name":null,"funder_award_id":"62372136","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7476944060","display_name":null,"funder_award_id":"BK20231337","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Semi-supervised":[0],"learning":[1,25,90],"can":[2,156,224],"leverage":[3],"both":[4],"labeled":[5],"and":[6,58,96,105,177,190,250,256],"unlabeled":[7],"samples":[8,50,135],"simultaneously":[9],"to":[10,202,216,229,235],"improve":[11],"performance.":[12],"However,":[13],"existing":[14],"methods":[15],"often":[16,69],"present":[17],"the":[18,30,34,40,60,71,102,116,127,132,153,158,166,181,186,204,221,254],"following":[19],"issues:":[20],"(1)":[21],"The":[22,45],"emphasis":[23],"of":[24,37,62,73,108,160,188,207,258],"is":[26,113,169],"put":[27],"on":[28,64,209],"either":[29],"similarity":[31,46,106],"structures":[32,47,107,176],"or":[33],"regression":[35,103,143,154,182],"losses":[36,104,144,155],"data,":[38],"neglecting":[39],"interaction":[41],"between":[42,134],"them.":[43],"(2)":[44],"among":[48],"boundary":[49,148,163],"might":[51],"be":[52,227],"unreliable,":[53],"which":[54,99],"misleads":[55],"label":[56,167],"propagation":[57,159],"impairs":[59],"performance":[61],"models":[63],"out-of-sample":[65],"data.":[66,109],"(3)":[67],"They":[68],"involve":[70],"inverses":[72],"high-order":[74],"matrices,":[75],"making":[76,142,213],"them":[77],"inefficient":[78],"in":[79,162],"computation.":[80],"To":[81],"overcome":[82],"these":[83],"issues,":[84],"we":[85],"propose":[86],"a":[87],"scalable":[88,215],"semi-supervised":[89],"framework":[91],"with":[92,121,242],"Discriminative":[93],"Label":[94],"Propagation":[95],"Correction":[97],"(DLPC),":[98],"collaboratively":[100],"exploits":[101],"Particularly,":[110],"each":[111],"sample":[112,210],"projected":[114],"onto":[115],"independent":[117],"class":[118],"labels":[119,161,189],"associated":[120],"nonnegative":[122],"adjustment":[123],"vectors":[124],"rather":[125],"than":[126],"propagated":[128,171],"labels,":[129],"such":[130],"that":[131],"distances":[133],"from":[136,151],"different":[137],"classes":[138],"are":[139],"naturally":[140],"enlarged,":[141],"more":[145],"effective":[146],"for":[147,248],"samples.":[149],"Benefiting":[150],"this,":[152],"guide":[157],"areas.":[164],"Thus,":[165],"information":[168],"first":[170],"through":[172],"dynamically":[173],"optimized":[174],"graph":[175],"then":[178],"corrected":[179],"by":[180],"losses,":[183],"effectively":[184],"improving":[185],"quality":[187],"facilitating":[191],"feature":[192],"projection":[193],"learning.":[194],"Furthermore,":[195],"an":[196,239],"accelerated":[197],"solution":[198],"has":[199,245],"been":[200,246],"developed":[201],"reduce":[203],"computational":[205],"costs":[206],"DLPC":[208,223,259],"scales,":[211],"thereby":[212],"it":[214],"relatively":[217],"large-scale":[218],"problems.":[219],"Moreover,":[220],"proposed":[222],"not":[225],"only":[226],"applied":[228],"single-view":[230],"scenarios":[231],"but":[232],"also":[233],"extended":[234],"multi-view":[236],"tasks.":[237],"Additionally,":[238],"optimization":[240],"strategy":[241],"fast":[243],"convergence":[244],"presented":[247],"DLPC,":[249],"extensive":[251],"experiments":[252],"demonstrate":[253],"effectiveness":[255],"superiority":[257],"over":[260],"state-of-the-art":[261],"competitors.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-01-21T00:00:00"}