{"id":"https://openalex.org/W4323338297","doi":"https://doi.org/10.1109/tpami.2023.3250323","title":"Clustered Task-Aware Meta-Learning by Learning From Learning Paths","display_name":"Clustered Task-Aware Meta-Learning by Learning From Learning Paths","publication_year":2023,"publication_date":"2023-03-06","ids":{"openalex":"https://openalex.org/W4323338297","doi":"https://doi.org/10.1109/tpami.2023.3250323","pmid":"https://pubmed.ncbi.nlm.nih.gov/37028045"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3250323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3250323","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089832695","display_name":"Danni Peng","orcid":"https://orcid.org/0000-0003-0884-9597"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Danni Peng","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0003-0884-9597","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082984558","display_name":"Sinno Jialin Pan","orcid":"https://orcid.org/0000-0001-6565-3836"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]},{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK","SG"],"is_corresponding":false,"raw_author_name":"Sinno Jialin Pan","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Singapore","Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-6565-3836","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5713,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.85592909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"45","issue":"8","first_page":"9426","last_page":"9438"},"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":1.0,"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":1.0,"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":0.9968000054359436,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9927999973297119,"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/computer-science","display_name":"Computer science","score":0.8158725500106812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6627290844917297},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.6385973691940308},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6323506832122803},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.6168161034584045},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.5773547887802124},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.546542227268219},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5230068564414978},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5065547227859497},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4811650216579437},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47689250111579895},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.44220244884490967},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43696409463882446},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43532097339630127}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8158725500106812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6627290844917297},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.6385973691940308},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6323506832122803},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.6168161034584045},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.5773547887802124},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.546542227268219},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5230068564414978},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5065547227859497},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4811650216579437},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47689250111579895},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.44220244884490967},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43696409463882446},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43532097339630127},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tpami.2023.3250323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3250323","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:37028045","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37028045","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:dr.ntu.edu.sg:10356/172181","is_oa":false,"landing_page_url":"https://hdl.handle.net/10356/172181","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320766","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W1542791059","https://openalex.org/W1797268635","https://openalex.org/W1846799578","https://openalex.org/W2020107577","https://openalex.org/W2027731328","https://openalex.org/W2047643928","https://openalex.org/W2067713319","https://openalex.org/W2219888463","https://openalex.org/W2533598788","https://openalex.org/W2560647685","https://openalex.org/W2787035179","https://openalex.org/W2963433607","https://openalex.org/W2963588172","https://openalex.org/W2963943197","https://openalex.org/W2964105864","https://openalex.org/W2964206659","https://openalex.org/W2964983698","https://openalex.org/W2990761674","https://openalex.org/W2995060963","https://openalex.org/W3034354010","https://openalex.org/W3043239945","https://openalex.org/W3080670519","https://openalex.org/W3081320135","https://openalex.org/W3092600962","https://openalex.org/W3095891659","https://openalex.org/W3106539628","https://openalex.org/W3108975329","https://openalex.org/W3112261659","https://openalex.org/W3138988683","https://openalex.org/W3153189161","https://openalex.org/W3177379791","https://openalex.org/W3202188231","https://openalex.org/W4294646197","https://openalex.org/W6638319203","https://openalex.org/W6638677478","https://openalex.org/W6685380521","https://openalex.org/W6717367658","https://openalex.org/W6717697761","https://openalex.org/W6736057607","https://openalex.org/W6741217325","https://openalex.org/W6743661861","https://openalex.org/W6743755419","https://openalex.org/W6744107841","https://openalex.org/W6746824174","https://openalex.org/W6747943641","https://openalex.org/W6748284727","https://openalex.org/W6750254146","https://openalex.org/W6751281049","https://openalex.org/W6751959828","https://openalex.org/W6752040014","https://openalex.org/W6752232076","https://openalex.org/W6753311412","https://openalex.org/W6755950020","https://openalex.org/W6756727096","https://openalex.org/W6758126075","https://openalex.org/W6760378562","https://openalex.org/W6763049584","https://openalex.org/W6763120227","https://openalex.org/W6764592398","https://openalex.org/W6766092863","https://openalex.org/W6767291801","https://openalex.org/W6771124855","https://openalex.org/W6771260093","https://openalex.org/W6771847183","https://openalex.org/W6771876938","https://openalex.org/W6782534648","https://openalex.org/W6782868315","https://openalex.org/W6784743763","https://openalex.org/W6784924269","https://openalex.org/W6787858355","https://openalex.org/W6792296156","https://openalex.org/W6798414287"],"related_works":["https://openalex.org/W2237537322","https://openalex.org/W2950678851","https://openalex.org/W4301248618","https://openalex.org/W1488960379","https://openalex.org/W4319075079","https://openalex.org/W2165343651","https://openalex.org/W2242427765","https://openalex.org/W2075830955","https://openalex.org/W3093147807","https://openalex.org/W4287637345"],"abstract_inverted_index":{"To":[0,25,158],"enable":[1],"effective":[2],"learning":[3,99,106,122,172],"of":[4,30,115,128,194],"new":[5],"tasks":[6,19],"with":[7,20,72,91],"only":[8],"a":[9,21,85,113,131,165,175],"few":[10],"examples,":[11],"meta-learning":[12],"acquires":[13],"common":[14,109],"knowledge":[15],"from":[16,62,95,107],"the":[17,28,52,63,68,75,108,147,170,192],"existing":[18],"globally":[22],"shared":[23],"meta-learner.":[24,54],"further":[26,159],"address":[27],"problem":[29],"task":[31,42,59,92,105,156],"heterogeneity,":[32],"recent":[33],"developments":[34],"balance":[35],"between":[36],"customization":[37],"and":[38,98,111,144,149,188],"generalization":[39],"by":[40],"incorporating":[41],"clustering":[43,143],"to":[44,48,51,74,168,197],"generate":[45],"task-aware":[46],"modulation":[47],"be":[49],"applied":[50],"global":[53],"However,":[55],"these":[56],"methods":[57],"learn":[58],"representation":[60,93,139],"mostly":[61],"features":[64,97],"ofinput":[65],"data,":[66],"while":[67],"task-specific":[69],"optimization":[70],"process":[71,173],"respect":[73],"base-learner":[76],"is":[77],"often":[78],"neglected.":[79],"In":[80],"this":[81,121,126],"work,":[82],"we":[83,135,163],"propose":[84],"Clustered":[86],"Task-Aware":[87],"Meta-Learning":[88],"(CTML)":[89],"framework":[90],"learned":[94],"both":[96],"paths.":[100],"We":[101,200],"first":[102],"conduct":[103],"rehearsed":[104,171],"initialization,":[110],"collect":[112],"set":[114,127],"geometric":[116],"quantities":[117],"that":[118],"adequately":[119],"describes":[120],"path.":[123],"By":[124],"inputting":[125],"values":[129],"into":[130],"meta":[132],"path":[133,138,148],"learner,":[134],"automatically":[136],"abstract":[137],"optimized":[140],"for":[141],"downstream":[142],"modulation.":[145],"Aggregating":[146],"feature":[150],"representations":[151],"results":[152],"in":[153],"an":[154],"improved":[155],"representation.":[157],"improve":[160],"inference":[161],"efficiency,":[162],"devise":[164],"shortcut":[166],"tunnel":[167],"bypass":[169],"at":[174,204],"meta-testing":[176],"time.":[177],"Extensive":[178],"experiments":[179],"on":[180],"two":[181],"real-world":[182],"application":[183],"domains:":[184],"few-shot":[185],"image":[186],"classification":[187],"cold-start":[189],"recommendation":[190],"demonstrate":[191],"superiority":[193],"CTML":[195],"compared":[196],"state-of-the-art":[198],"methods.":[199],"provide":[201],"our":[202],"code":[203],"https://github.com/didiya0825.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
