{"id":"https://openalex.org/W4414359574","doi":"https://doi.org/10.24963/ijcai.2025/545","title":"Pseudo-Label Reconstruction for Partial Multi-Label Learning","display_name":"Pseudo-Label Reconstruction for Partial Multi-Label Learning","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414359574","doi":"https://doi.org/10.24963/ijcai.2025/545"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/545","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","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":"https://openalex.org/A5100401934","display_name":"Yu Chen","orcid":"https://orcid.org/0000-0001-5468-1380"},"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":"Yu Chen","raw_affiliation_strings":["Guangdong University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101907359","display_name":"Li Fang","orcid":"https://orcid.org/0000-0002-4876-6975"},"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":"Fang Li","raw_affiliation_strings":["Guangdong University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050428376","display_name":"Na Han","orcid":"https://orcid.org/0000-0002-9639-7633"},"institutions":[{"id":"https://openalex.org/I4210122543","display_name":"Guangdong Polytechnic Normal University","ror":"https://ror.org/02pcb5m77","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210122543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Han","raw_affiliation_strings":["Guangdong Polytechnic Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Polytechnic Normal University","institution_ids":["https://openalex.org/I4210122543"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033043081","display_name":"Guanbin Li","orcid":"https://orcid.org/0000-0002-2486-2890"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanbin Li","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007825395","display_name":"Hongbo Gao","orcid":"https://orcid.org/0000-0002-5271-1280"},"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":"Hongbo Gao","raw_affiliation_strings":["Institute of Advanced Technology, University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Advanced Technology, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003029072","display_name":"Sixian Chan","orcid":"https://orcid.org/0000-0001-8916-1174"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sixian Chan","raw_affiliation_strings":["Zhejiang University Of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University Of Technology","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052008856","display_name":"Xiaozhao Fang","orcid":"https://orcid.org/0000-0001-8440-1765"},"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":"Xiaozhao Fang","raw_affiliation_strings":["Guangdong University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4896","last_page":"4904"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9584000110626221,"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"}},"topics":[{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9584000110626221,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9254000186920166,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.7401999831199646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6283000111579895},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.554099977016449},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5325000286102295},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5037000179290771},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.36880001425743103},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.36500000953674316},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.3409000039100647}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7401999831199646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6895999908447266},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6283000111579895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5740000009536743},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.554099977016449},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5325000286102295},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5037000179290771},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.36880001425743103},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.36500000953674316},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3474999964237213},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3237000107765198},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.31839999556541443},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C64708745","wikidata":"https://www.wikidata.org/wiki/Q2998010","display_name":"Partial correlation","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/545","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"Partial":[1],"Multi-Label":[2],"Learning":[3],"(PML),":[4],"each":[5],"instance":[6,30,33,57,99,105,110],"is":[7],"associated":[8],"with":[9,19,51,98],"a":[10,52,75,88],"candidate":[11,38,64,91],"label":[12,68,92],"set":[13],"containing":[14],"multiple":[15],"relevant":[16],"labels":[17,65,134],"along":[18],"other":[20],"false":[21],"positive":[22],"labels.":[23],"Currently,":[24],"most":[25],"PML":[26,77],"methods":[27],"directly":[28],"extract":[29,102],"correlation":[31,58,111],"from":[32,62],"features":[34,100],"while":[35],"ignoring":[36],"the":[37,63,123,130,139,149],"labels,":[39],"which":[40,95],"may":[41],"contain":[42],"more":[43,55,103],"discriminative":[44],"instance-related":[45],"information.":[46],"This":[47],"paper":[48],"argues":[49],"that,":[50],"well-designed":[53],"model,":[54],"accurate":[56],"can":[59],"be":[60],"mined":[61],"to":[66,101,115,128],"facilitate":[67],"disambiguation.":[69],"To":[70],"this":[71],"end,":[72],"we":[73,85,108],"propose":[74,87],"novel":[76,89],"method":[78],"based":[79],"on":[80],"pseudo-label":[81],"reconstruction":[82,93,113],"(PML-PLR).":[83],"Specifically,":[84],"first":[86],"orthogonal":[90],"method,":[94],"jointly":[96],"optimizes":[97],"consistent":[104],"correlation.":[106],"Then,":[107],"use":[109],"as":[112],"coefficient":[114],"reconstruct":[116],"pseudo-labels.":[117,142],"Subsequently,":[118],"through":[119],"local":[120],"manifold":[121],"learning,":[122],"reconstructed":[124],"pseudo-labels":[125],"are":[126],"leveraged":[127],"propagate":[129],"consistency":[131],"relationship":[132],"between":[133],"and":[135,145],"instances,":[136],"thereby":[137],"improving":[138],"accuracy":[140],"of":[141],"Extensive":[143],"experiments":[144],"analyses":[146],"demonstrate":[147],"that":[148],"proposed":[150],"PML-PLR":[151],"outperforms":[152],"state-of-the-art":[153],"methods.":[154]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}