{"id":"https://openalex.org/W4389609591","doi":"https://doi.org/10.1007/s10994-023-06387-w","title":"Understanding transfer learning and gradient-based meta-learning techniques","display_name":"Understanding transfer learning and gradient-based meta-learning techniques","publication_year":2023,"publication_date":"2023-12-12","ids":{"openalex":"https://openalex.org/W4389609591","doi":"https://doi.org/10.1007/s10994-023-06387-w"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-023-06387-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-023-06387-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-023-06387-w.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-023-06387-w.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009353781","display_name":"Mike Huisman","orcid":"https://orcid.org/0000-0001-9215-2973"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Mike Huisman","raw_affiliation_strings":["LIACS, Leiden University, Niels Bohrweg 1, 2333CA, Leiden, The Netherlands"],"affiliations":[{"raw_affiliation_string":"LIACS, Leiden University, Niels Bohrweg 1, 2333CA, Leiden, The Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085542421","display_name":"Aske Plaat","orcid":"https://orcid.org/0000-0001-7202-3322"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Aske Plaat","raw_affiliation_strings":["LIACS, Leiden University, Niels Bohrweg 1, 2333CA, Leiden, The Netherlands"],"affiliations":[{"raw_affiliation_string":"LIACS, Leiden University, Niels Bohrweg 1, 2333CA, Leiden, The Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009236758","display_name":"Jan N. van Rijn","orcid":"https://orcid.org/0000-0003-2898-2168"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Jan N. van Rijn","raw_affiliation_strings":["LIACS, Leiden University, Niels Bohrweg 1, 2333CA, Leiden, The Netherlands"],"affiliations":[{"raw_affiliation_string":"LIACS, Leiden University, Niels Bohrweg 1, 2333CA, Leiden, The Netherlands","institution_ids":["https://openalex.org/I121797337"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5009353781"],"corresponding_institution_ids":["https://openalex.org/I121797337"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.5734,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.86861694,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"113","issue":"7","first_page":"4113","last_page":"4132"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9980000257492065,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"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":0.7675002813339233},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.7461915016174316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7216091156005859},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7074439525604248},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.6463125944137573},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6075276136398315},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5558673143386841},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5423352122306824},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5396983027458191},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4329816699028015},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4119328260421753},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.0857740044593811},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07606250047683716},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06606036424636841}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7675002813339233},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.7461915016174316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7216091156005859},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7074439525604248},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.6463125944137573},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6075276136398315},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5558673143386841},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5423352122306824},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5396983027458191},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4329816699028015},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4119328260421753},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0857740044593811},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07606250047683716},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06606036424636841},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10994-023-06387-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-023-06387-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-023-06387-w.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10994-023-06387-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-023-06387-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-023-06387-w.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7400000095367432}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320929","display_name":"Universiteit Leiden","ror":"https://ror.org/027bh9e22"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4389609591.pdf"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W2108598243","https://openalex.org/W2126204609","https://openalex.org/W2145339207","https://openalex.org/W2163605009","https://openalex.org/W2257979135","https://openalex.org/W2604763608","https://openalex.org/W2919115771","https://openalex.org/W2963070905","https://openalex.org/W2974885182","https://openalex.org/W3009081299","https://openalex.org/W3092053846","https://openalex.org/W3108975329","https://openalex.org/W3122520870","https://openalex.org/W3154662890","https://openalex.org/W3154934604","https://openalex.org/W4212979146","https://openalex.org/W4256520039","https://openalex.org/W4297792979","https://openalex.org/W6638319203","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6743661861","https://openalex.org/W6753311412","https://openalex.org/W6758126075","https://openalex.org/W6776331362"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W4283332751","https://openalex.org/W3163412989"],"abstract_inverted_index":{"Abstract":[0],"Deep":[1],"neural":[2],"networks":[3,34],"can":[4,232],"yield":[5],"good":[6],"performance":[7,126],"on":[8,61,118,235],"various":[9,53],"tasks":[10,62,229],"but":[11],"often":[12],"require":[13],"large":[14],"amounts":[15],"of":[16,32,39,97,110,114,150,215,238],"data":[17,66,152,175],"to":[18,28,47,212,225,227],"train":[19],"them.":[20],"Meta-learning":[21],"received":[22],"considerable":[23],"attention":[24],"as":[25,92,106,154,193],"one":[26,70,96,156],"approach":[27],"improve":[29],"the":[30,69,98,107,124,155,165,169,190,196,236,239],"generalization":[31],"these":[33],"from":[35,63],"a":[36,64,74,79],"limited":[37],"amount":[38],"data.":[40],"Whilst":[41],"meta-learning":[42,89,101,133],"techniques":[43,90],"have":[44],"been":[45],"observed":[46,125],"be":[48,83],"successful":[49],"at":[50],"this":[51,182,213],"in":[52,147,180],"scenarios,":[54],"recent":[55],"results":[56],"suggest":[57],"that":[58,76,113,139,163,189],"when":[59],"evaluated":[60],"different":[65],"distribution":[67,153,218],"than":[68,86,204],"used":[71,157],"for":[72,144,158,184],"training,":[73],"baseline":[75,198],"simply":[77],"finetunes":[78],"pre-trained":[80,191],"network":[81],"may":[82,223],"more":[84,87,200],"effective":[85],"complicated":[88],"such":[91],"MAML,":[93,130],"which":[94],"is":[95,104],"most":[99],"popular":[100],"techniques.":[102],"This":[103],"surprising":[105],"learning":[108],"behaviour":[109],"MAML":[111,140,208,220],"mimics":[112],"finetuning:":[115],"both":[116,164],"rely":[117],"re-using":[119],"learned":[120,206,240],"features.":[121,241],"We":[122],"investigate":[123],"differences":[127],"between":[128],"finetuning,":[129],"and":[131,137,141,168,202,209,217,221],"another":[132],"technique":[134],"called":[135],"Reptile,":[136],"show":[138,162,188],"Reptile":[142,222],"specialize":[143],"fast":[145],"adaptation":[146],"low-data":[148],"regimes":[149],"similar":[151],"training.":[159],"Our":[160],"findings":[161],"output":[166],"layer":[167],"noisy":[170],"training":[171],"conditions":[172],"induced":[173],"by":[174,195,207],"scarcity":[176],"play":[177],"important":[178],"roles":[179],"facilitating":[181],"specialization":[183],"MAML.":[185],"Lastly,":[186],"we":[187],"features":[192],"obtained":[194],"finetuning":[197,231],"are":[199],"diverse":[201],"discriminative":[203],"those":[205],"Reptile.":[210],"Due":[211],"lack":[214],"diversity":[216,237],"specialization,":[219],"fail":[224],"generalize":[226],"out-of-distribution":[228],"whereas":[230],"fall":[233],"back":[234]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}