{"id":"https://openalex.org/W4312389556","doi":"https://doi.org/10.1109/access.2022.3228829","title":"Meta-Learning Amidst Heterogeneity and Ambiguity","display_name":"Meta-Learning Amidst Heterogeneity and Ambiguity","publication_year":2022,"publication_date":"2022-12-12","ids":{"openalex":"https://openalex.org/W4312389556","doi":"https://doi.org/10.1109/access.2022.3228829"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3228829","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3228829","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2022.3228829","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063479107","display_name":"Kyeongryeol Go","orcid":"https://orcid.org/0000-0002-1691-3344"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kyeongryeol Go","raw_affiliation_strings":["Superb AI Inc., Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-1691-3344","affiliations":[{"raw_affiliation_string":"Superb AI Inc., Seoul, South Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100620588","display_name":"Mingyu Kim","orcid":"https://orcid.org/0000-0001-5082-7223"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Mingyu Kim","raw_affiliation_strings":["Kim Jaechul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kim Jaechul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Seoul, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091674853","display_name":"Se-Young Yun","orcid":"https://orcid.org/0000-0001-6675-5113"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seyoung Yun","raw_affiliation_strings":["Kim Jaechul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-6675-5113","affiliations":[{"raw_affiliation_string":"Kim Jaechul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Seoul, South Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5063479107"],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.1389,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5675851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"11","issue":null,"first_page":"1578","last_page":"1592"},"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":0.9994000196456909,"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":0.9994000196456909,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9965999722480774,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9876999855041504,"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/ambiguity","display_name":"Ambiguity","score":0.8616769313812256},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7893104553222656},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.7186728715896606},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6916971206665039},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6206391453742981},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6082512140274048},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5878642797470093},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5777629613876343},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5681743621826172},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.4385632872581482}],"concepts":[{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.8616769313812256},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7893104553222656},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.7186728715896606},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6916971206665039},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6206391453742981},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6082512140274048},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5878642797470093},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5777629613876343},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5681743621826172},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.4385632872581482},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2022.3228829","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3228829","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2ebc35050a0b46cf941b785e6a839810","is_oa":true,"landing_page_url":"https://doaj.org/article/2ebc35050a0b46cf941b785e6a839810","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 1578-1592 (2023)","raw_type":"article"},{"id":"pmh:oai:koasas.kaist.ac.kr:10203/304794","is_oa":false,"landing_page_url":"http://hdl.handle.net/10203/304794","pdf_url":null,"source":{"id":"https://openalex.org/S4306402435","display_name":"KAIST Institutional Repository (KAIST)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I157485424","host_organization_name":"Korea Advanced Institute of Science and Technology","host_organization_lineage":["https://openalex.org/I157485424"],"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":"Article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3228829","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3228829","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4099999964237213,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W1571870753","https://openalex.org/W2047643928","https://openalex.org/W2097998348","https://openalex.org/W2117539524","https://openalex.org/W2187089797","https://openalex.org/W2625674597","https://openalex.org/W2964105864","https://openalex.org/W2987861506","https://openalex.org/W3003257820","https://openalex.org/W3037099311","https://openalex.org/W3120637139","https://openalex.org/W3160331490","https://openalex.org/W3198381997","https://openalex.org/W3209696639","https://openalex.org/W4211049957","https://openalex.org/W4282813335","https://openalex.org/W6600609147","https://openalex.org/W6638677478","https://openalex.org/W6640963894","https://openalex.org/W6674385629","https://openalex.org/W6684770997","https://openalex.org/W6687045409","https://openalex.org/W6717697761","https://openalex.org/W6718362372","https://openalex.org/W6720057410","https://openalex.org/W6731412260","https://openalex.org/W6734030655","https://openalex.org/W6734451663","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6739901393","https://openalex.org/W6740364378","https://openalex.org/W6740879895","https://openalex.org/W6743661861","https://openalex.org/W6744627333","https://openalex.org/W6748107402","https://openalex.org/W6748284727","https://openalex.org/W6751281049","https://openalex.org/W6751453731","https://openalex.org/W6751959828","https://openalex.org/W6752040014","https://openalex.org/W6752796717","https://openalex.org/W6752968661","https://openalex.org/W6753311412","https://openalex.org/W6755318597","https://openalex.org/W6755477022","https://openalex.org/W6756440941","https://openalex.org/W6758711939","https://openalex.org/W6759172331","https://openalex.org/W6763049584","https://openalex.org/W6763424315","https://openalex.org/W6763918015","https://openalex.org/W6764592398","https://openalex.org/W6769908858","https://openalex.org/W6771326545","https://openalex.org/W6771847183","https://openalex.org/W6779702771","https://openalex.org/W6779886411","https://openalex.org/W6781903740","https://openalex.org/W6782680132","https://openalex.org/W6784057640","https://openalex.org/W6789117725","https://openalex.org/W6790291204","https://openalex.org/W6791136995","https://openalex.org/W6793285144","https://openalex.org/W6796663145","https://openalex.org/W6803413663","https://openalex.org/W6803869602","https://openalex.org/W6809849193","https://openalex.org/W6810302345","https://openalex.org/W6838655624","https://openalex.org/W6839443103","https://openalex.org/W6840415919"],"related_works":["https://openalex.org/W1488960379","https://openalex.org/W3004751640","https://openalex.org/W4319075079","https://openalex.org/W4287637345","https://openalex.org/W3093147807","https://openalex.org/W1530810814","https://openalex.org/W4287992200","https://openalex.org/W3105253998","https://openalex.org/W4385484791","https://openalex.org/W4320498382"],"abstract_inverted_index":{"Meta-learning":[0,69],"aims":[1],"to":[2,26,36,85,107,109],"learn":[3],"a":[4,31,64],"model":[5],"that":[6,30,75],"can":[7],"handle":[8],"multiple":[9],"tasks":[10,25],"generated":[11],"from":[12],"an":[13],"unknown":[14],"but":[15],"shared":[16],"distribution.":[17],"However,":[18],"typical":[19],"meta-learning":[20,66],"algorithms":[21],"have":[22],"assumed":[23],"the":[24,38,99],"be":[27],"similar":[28],"such":[29],"single":[32],"meta-learner":[33],"is":[34,55],"sufficient":[35],"aggregate":[37],"variations":[39],"in":[40,79,93],"all":[41],"aspects.":[42],"In":[43,59],"addition,":[44],"there":[45],"has":[46],"been":[47],"less":[48],"consideration":[49],"of":[50,101],"uncertainty":[51],"when":[52],"limited":[53],"information":[54],"given":[56],"as":[57],"context.":[58],"this":[60],"paper,":[61],"we":[62,97],"devise":[63],"novel":[65],"framework,":[67],"called":[68],"Amidst":[70],"Heterogeneity":[71],"and":[72,95,113],"Ambiguity":[73],"(MAHA),":[74],"outperforms":[76],"previous":[77],"works":[78],"prediction":[80],"based":[81],"on":[82],"its":[83],"ability":[84],"task":[86,111],"identification.":[87],"By":[88],"extensively":[89],"conducting":[90],"several":[91],"experiments":[92],"regression":[94],"classification,":[96],"demonstrate":[98],"validity":[100],"our":[102],"model,":[103],"which":[104],"turns":[105],"out":[106],"generalize":[108],"both":[110],"heterogeneity":[112],"ambiguity.":[114]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}