{"id":"https://openalex.org/W4402502616","doi":"https://doi.org/10.48550/arxiv.2408.10046","title":"Exploiting Fine-Grained Prototype Distribution for Boosting Unsupervised Class Incremental Learning","display_name":"Exploiting Fine-Grained Prototype Distribution for Boosting Unsupervised Class Incremental Learning","publication_year":2024,"publication_date":"2024-08-19","ids":{"openalex":"https://openalex.org/W4402502616","doi":"https://doi.org/10.48550/arxiv.2408.10046"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2408.10046","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.10046","pdf_url":"https://arxiv.org/pdf/2408.10046","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2408.10046","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100440961","display_name":"Jiaming Liu","orcid":"https://orcid.org/0000-0001-5697-1656"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liu, Jiaming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107942136","display_name":"Hong-Yuan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Hongyuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025958247","display_name":"Zhili Qin","orcid":"https://orcid.org/0009-0004-8030-9522"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Zhili","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110979192","display_name":"Wei Han","orcid":"https://orcid.org/0000-0002-1855-6379"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114073968","display_name":"Yulu Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Yulu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102515645","display_name":"Qinli Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Qinli","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5007616841","display_name":"Junming Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Junming","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100440961"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.8452000021934509,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.8452000021934509,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.819599986076355,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.7077000141143799,"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/boosting","display_name":"Boosting (machine learning)","score":0.8971015810966492},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5840290784835815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5583215951919556},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.539874792098999},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48354506492614746},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.434432715177536},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.41580480337142944}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8971015810966492},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5840290784835815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5583215951919556},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.539874792098999},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48354506492614746},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.434432715177536},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.41580480337142944}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2408.10046","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.10046","pdf_url":"https://arxiv.org/pdf/2408.10046","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2408.10046","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2408.10046","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2408.10046","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.10046","pdf_url":"https://arxiv.org/pdf/2408.10046","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402502616.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3082059448","https://openalex.org/W4313640622","https://openalex.org/W3196155444","https://openalex.org/W4321844043","https://openalex.org/W3210156800","https://openalex.org/W4390062853","https://openalex.org/W4297883248","https://openalex.org/W4255830763","https://openalex.org/W1583266947","https://openalex.org/W4286799911"],"abstract_inverted_index":{"The":[0,52],"dynamic":[1],"nature":[2],"of":[3,23,46,54,78,119,140],"open-world":[4],"scenarios":[5],"has":[6],"attracted":[7],"more":[8,43],"attention":[9],"to":[10,92,103],"class":[11,48,79,96],"incremental":[12,49],"learning":[13,50],"(CIL).":[14],"However,":[15],"existing":[16,109],"CIL":[17],"methods":[18],"typically":[19],"presume":[20],"the":[21,28,76,94,117,125,138,141],"availability":[22],"complete":[24],"ground-truth":[25],"labels":[26],"throughout":[27],"training":[29],"process,":[30],"an":[31],"assumption":[32],"rarely":[33],"met":[34],"in":[35,59],"practical":[36],"applications.":[37],"Consequently,":[38],"this":[39,56],"paper":[40],"explores":[41],"a":[42,86,101],"challenging":[44],"problem":[45,57],"unsupervised":[47,95],"(UCIL).":[51],"essence":[53],"addressing":[55],"lies":[58],"effectively":[60],"capturing":[61],"comprehensive":[62],"feature":[63],"representations":[64],"and":[65,108,115],"discovering":[66],"unknown":[67],"novel":[68,107],"classes.":[69],"To":[70],"achieve":[71],"this,":[72],"we":[73,99],"first":[74],"model":[75],"knowledge":[77,114],"distribution":[80],"by":[81],"exploiting":[82],"fine-grained":[83],"prototypes.":[84],"Subsequently,":[85],"granularity":[87],"alignment":[88],"technique":[89],"is":[90],"introduced":[91],"enhance":[93],"discovery.":[97],"Additionally,":[98],"proposed":[100,142],"strategy":[102],"minimize":[104],"overlap":[105],"between":[106],"classes,":[110],"thereby":[111],"preserving":[112],"historical":[113],"mitigating":[116],"phenomenon":[118],"catastrophic":[120],"forgetting.":[121],"Extensive":[122],"experiments":[123],"on":[124],"five":[126],"datasets":[127],"demonstrate":[128],"that":[129],"our":[130],"approach":[131],"significantly":[132],"outperforms":[133],"current":[134],"state-of-the-art":[135],"methods,":[136],"indicating":[137],"effectiveness":[139],"method.":[143]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2024-09-13T00:00:00"}
