{"id":"https://openalex.org/W3128395934","doi":"https://doi.org/10.1109/icoin50884.2021.9334003","title":"Clustering-Guided Incremental Learning of Tasks","display_name":"Clustering-Guided Incremental Learning of Tasks","publication_year":2021,"publication_date":"2021-01-13","ids":{"openalex":"https://openalex.org/W3128395934","doi":"https://doi.org/10.1109/icoin50884.2021.9334003","mag":"3128395934"},"language":"en","primary_location":{"id":"doi:10.1109/icoin50884.2021.9334003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icoin50884.2021.9334003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Information Networking (ICOIN)","raw_type":"proceedings-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":"Yoonhee Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yoonhee Kim","raw_affiliation_strings":["School of Computer Science and Engineering, Chung-Ang University, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Chung-Ang University, South Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074532898","display_name":"Eunwoo Kim","orcid":"https://orcid.org/0000-0003-0840-0044"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Eunwoo Kim","raw_affiliation_strings":["School of Computer Science and Engineering, Chung-Ang University, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Chung-Ang University, South Korea","institution_ids":["https://openalex.org/I67900169"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I67900169"],"apc_list":null,"apc_paid":null,"fwci":0.14,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51990267,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"417","last_page":"421"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9973999857902527,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9807999730110168,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.9266571998596191},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8240430355072021},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7070539593696594},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7014551162719727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6163909435272217},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.5609797239303589},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5363266468048096},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.524041473865509},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.44006645679473877},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07754635810852051}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.9266571998596191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8240430355072021},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7070539593696594},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7014551162719727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6163909435272217},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.5609797239303589},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5363266468048096},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.524041473865509},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.44006645679473877},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07754635810852051},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icoin50884.2021.9334003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icoin50884.2021.9334003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Information Networking (ICOIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1535804263","https://openalex.org/W1682403713","https://openalex.org/W1797268635","https://openalex.org/W1972420097","https://openalex.org/W2097749765","https://openalex.org/W2117539524","https://openalex.org/W2127218421","https://openalex.org/W2138011018","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2473930607","https://openalex.org/W2533598788","https://openalex.org/W2560647685","https://openalex.org/W2583761661","https://openalex.org/W2624871570","https://openalex.org/W2796394093","https://openalex.org/W2902625698","https://openalex.org/W2913340405","https://openalex.org/W2963037989","https://openalex.org/W2963072899","https://openalex.org/W2963540014","https://openalex.org/W2963674932","https://openalex.org/W2963677766","https://openalex.org/W2963835211","https://openalex.org/W2964189064","https://openalex.org/W4229706055","https://openalex.org/W6628973269","https://openalex.org/W6678914141","https://openalex.org/W6730146409","https://openalex.org/W6732467815","https://openalex.org/W6738279954","https://openalex.org/W6739365718","https://openalex.org/W6742852309","https://openalex.org/W6757384668"],"related_works":["https://openalex.org/W4287067590","https://openalex.org/W3186262193","https://openalex.org/W3192176272","https://openalex.org/W4297634446","https://openalex.org/W4391158518","https://openalex.org/W4381322349","https://openalex.org/W3085307110","https://openalex.org/W3157400488","https://openalex.org/W4382021137","https://openalex.org/W2892655153"],"abstract_inverted_index":{"Incremental":[0],"deep":[1,20],"learning":[2,91],"aims":[3],"to":[4,23,53,72,113,125,133,165],"learn":[5,148],"a":[6,19,59,73,88,110,115,130,141,149,179,186],"sequence":[7],"of":[8,27,33,76,103,117,156,174,188],"tasks":[9,34,138,159],"while":[10,98],"avoiding":[11],"forgetting":[12,97],"their":[13],"knowledge.":[14],"One":[15],"na\u00efve":[16],"approach":[17,47,92,108,132,169,176],"using":[18],"architecture":[21,29,121],"is":[22,38],"increase":[24],"the":[25,28,31,46,101,135,154,157,162,172,175],"capacity":[26,102],"as":[30],"number":[32,187],"increases.":[35],"However,":[36],"this":[37],"followed":[39],"by":[40,139],"heavy":[41],"memory":[42],"consumption":[43],"and":[44],"makes":[45],"not":[48,99],"practical.":[49],"If":[50],"we":[51,62,86,147,152],"attempt":[52],"avoid":[54],"such":[55],"an":[56,104,120],"issue":[57],"with":[58,161,185],"fixed":[60,181],"capacity,":[61],"encounter":[63],"another":[64],"challenging":[65],"problem":[66],"called":[67],"catastrophic":[68,96],"forgetting,":[69],"which":[70],"leads":[71],"notable":[74],"degradation":[75],"performance":[77],"on":[78],"previously":[79],"learned":[80],"tasks.":[81],"To":[82],"overcome":[83],"these":[84],"problems,":[85],"propose":[87],"clustering-guided":[89],"incremental":[90],"that":[93,192],"can":[94],"mitigate":[95],"increasing":[100],"architecture.":[105,182],"The":[106],"proposed":[107],"adopts":[109],"parameter-splitting":[111],"strategy":[112],"assign":[114],"subset":[116],"parameters":[118],"in":[119,178],"for":[122],"each":[123],"task":[124,164],"prevent":[126],"forgetting.":[127],"It":[128],"uses":[129],"clustering":[131],"discover":[134],"relationship":[136],"between":[137],"storing":[140],"few":[142],"samples":[143],"per":[144],"task.":[145],"When":[146],"new":[150],"task,":[151],"utilize":[153],"knowledge":[155],"relevant":[158],"together":[160],"current":[163],"improve":[166],"performance.":[167],"This":[168],"could":[170],"maximize":[171],"efficiency":[173],"realized":[177],"single":[180],"Experimental":[183],"results":[184],"fine-grained":[189],"datasets":[190],"show":[191],"our":[193],"method":[194],"outperforms":[195],"existing":[196],"competitors.":[197]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}