{"id":"https://openalex.org/W4362692873","doi":"https://doi.org/10.1109/tnnls.2023.3262267","title":"Output Regularization With Cluster-Based Soft Targets","display_name":"Output Regularization With Cluster-Based Soft Targets","publication_year":2023,"publication_date":"2023-04-07","ids":{"openalex":"https://openalex.org/W4362692873","doi":"https://doi.org/10.1109/tnnls.2023.3262267","pmid":"https://pubmed.ncbi.nlm.nih.gov/37027269"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3262267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3262267","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5046093778","display_name":"Jian-Ping Mei","orcid":"https://orcid.org/0000-0003-1678-6215"},"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":"Jian-Ping Mei","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1678-6215","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102991891","display_name":"Wenhao Qiu","orcid":"https://orcid.org/0009-0005-9133-2450"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenhao Qiu","raw_affiliation_strings":["DiDi Global Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DiDi Global Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101821806","display_name":"Defang Chen","orcid":"https://orcid.org/0000-0003-0833-7401"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Defang Chen","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0833-7401","affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046836420","display_name":"Rui Yan","orcid":"https://orcid.org/0000-0003-0048-3092"},"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":"Rui Yan","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0048-3092","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100739538","display_name":"Jing Fan","orcid":"https://orcid.org/0000-0002-0140-7043"},"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":"Jing Fan","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.517,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71127899,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"35","issue":"8","first_page":"11463","last_page":"11474"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9993000030517578,"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/T12676","display_name":"Machine Learning and ELM","score":0.9993000030517578,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991000294685364,"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":0.9979000091552734,"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":0.6404615044593811},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.618497371673584},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.612614095211029},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5879352688789368},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5614911913871765},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.5411486029624939},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5256289839744568},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49333587288856506},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47601228952407837},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.44657060503959656},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3642348051071167},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2833125591278076}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6404615044593811},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.618497371673584},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.612614095211029},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5879352688789368},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5614911913871765},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.5411486029624939},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5256289839744568},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49333587288856506},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47601228952407837},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.44657060503959656},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3642348051071167},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2833125591278076}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3262267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3262267","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37027269","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37027269","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 neural networks and learning systems","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2468186984","display_name":null,"funder_award_id":"62072405","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3694722345","display_name":null,"funder_award_id":"U2030204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5769466829","display_name":null,"funder_award_id":"62276234","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6084565866","display_name":null,"funder_award_id":"LY20F020023","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1797268635","https://openalex.org/W1821462560","https://openalex.org/W1995450389","https://openalex.org/W2095705004","https://openalex.org/W2150593711","https://openalex.org/W2152161678","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2345474290","https://openalex.org/W2741943936","https://openalex.org/W2779692282","https://openalex.org/W2883725317","https://openalex.org/W2904170036","https://openalex.org/W2963446712","https://openalex.org/W2964137095","https://openalex.org/W2964159205","https://openalex.org/W2996970889","https://openalex.org/W2997770686","https://openalex.org/W3034576826","https://openalex.org/W3034695001","https://openalex.org/W3035524453","https://openalex.org/W3087124270","https://openalex.org/W3093209609","https://openalex.org/W3118608800","https://openalex.org/W3171007011","https://openalex.org/W6638319203","https://openalex.org/W6674330103","https://openalex.org/W6717772578","https://openalex.org/W6728550200","https://openalex.org/W6732696085","https://openalex.org/W6733814495","https://openalex.org/W6745136726","https://openalex.org/W6755069125","https://openalex.org/W6762913911","https://openalex.org/W6764051988","https://openalex.org/W6765939562","https://openalex.org/W6769906912","https://openalex.org/W6770196601","https://openalex.org/W6773005947","https://openalex.org/W6777265123","https://openalex.org/W6779997284","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2051058708","https://openalex.org/W1494268238","https://openalex.org/W154868527","https://openalex.org/W1983207144","https://openalex.org/W2490706771","https://openalex.org/W2480116122","https://openalex.org/W4255576661","https://openalex.org/W1516574938","https://openalex.org/W2625725254","https://openalex.org/W2563912921"],"abstract_inverted_index":{"While":[0],"supervised":[1],"learning":[2],"of":[3,43,130,140],"over-parameterized":[4],"neural":[5,96],"networks":[6],"achieved":[7],"state-of-the-art":[8],"performance":[9],"in":[10,60,92,113,126,160],"image":[11,131],"classification,":[12],"it":[13,56],"tends":[14],"to":[15,21,147],"over-fit":[16],"the":[17,44,114,174],"labeled":[18],"training":[19,37,98],"samples":[20,125],"give":[22],"inferior":[23],"generalization":[24],"ability.":[25],"Output":[26,80],"regularization":[27,63],"deals":[28],"with":[29,99,164],"over-fitting":[30],"by":[31,74,123],"using":[32],"soft":[33,77,101,120,170],"targets":[34,78,102,121,171],"as":[35],"additional":[36],"signals.":[38],"Although":[39],"clustering":[40,91],"is":[41],"one":[42],"most":[45],"fundamental":[46],"data":[47,152],"analysis":[48],"tools":[49],"for":[50,79,89],"discovering":[51],"general-purpose":[52],"and":[53,95,157],"data-driven":[54],"structures,":[55],"has":[57],"been":[58],"ignored":[59],"existing":[61],"output":[62,104],"approaches.":[64],"In":[65],"this":[66,70],"article,":[67],"we":[68,117,154],"leverage":[69],"underlying":[71],"structural":[72],"information":[73],"proposing":[75],"Cluster-based":[76],"Regularization":[81],"(CluOReg).":[82],"This":[83],"approach":[84],"provides":[85],"a":[86,109,138],"unified":[87],"way":[88],"simultaneous":[90],"embedding":[93],"space":[94],"classifier":[97],"cluster-based":[100,169],"via":[103],"regularization.":[105],"By":[106],"explicitly":[107],"calculating":[108],"class":[110],"relationship":[111],"matrix":[112],"cluster":[115],"space,":[116],"obtain":[118],"classwise":[119],"shared":[122],"all":[124],"each":[127],"class.":[128],"Results":[129],"classification":[132,161],"experiments":[133],"under":[134],"various":[135],"settings":[136],"on":[137],"number":[139],"benchmark":[141],"datasets":[142],"are":[143],"provided.":[144],"Without":[145],"resorting":[146],"external":[148],"models":[149],"or":[150],"designed":[151],"augmentation,":[153],"get":[155],"consistent":[156],"significant":[158],"reductions":[159],"error":[162],"compared":[163],"other":[165],"approaches,":[166],"demonstrating":[167],"that":[168],"effectively":[172],"complement":[173],"ground-truth":[175],"label.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
