{"id":"https://openalex.org/W3167936803","doi":"https://doi.org/10.1145/3449726.3459532","title":"Meta-learning for symbolic hyperparameter defaults","display_name":"Meta-learning for symbolic hyperparameter defaults","publication_year":2021,"publication_date":"2021-07-07","ids":{"openalex":"https://openalex.org/W3167936803","doi":"https://doi.org/10.1145/3449726.3459532","mag":"3167936803"},"language":"en","primary_location":{"id":"doi:10.1145/3449726.3459532","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3449726.3459532","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3449726.3459532&file=p151-gijsbers_suppl.pdf","source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3449726.3459532&file=p151-gijsbers_suppl.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081552858","display_name":"Pieter Gijsbers","orcid":"https://orcid.org/0000-0001-7346-8075"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Pieter Gijsbers","raw_affiliation_strings":["University of Eindhoven, Eindhoven, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Eindhoven, Eindhoven, Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019209786","display_name":"Florian Pfisterer","orcid":"https://orcid.org/0000-0001-8867-762X"},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Florian Pfisterer","raw_affiliation_strings":["Ludwig-Maximilians-University, Munich, Germany","Ludwig-Maximilians-University Munich, Germany#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ludwig-Maximilians-University, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]},{"raw_affiliation_string":"Ludwig-Maximilians-University Munich, Germany#TAB#","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","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":["Leiden University, Leiden, Netherlands","Leiden University Leiden  Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, Netherlands","institution_ids":["https://openalex.org/I121797337"]},{"raw_affiliation_string":"Leiden University Leiden  Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069072700","display_name":"Bernd Bischl","orcid":"https://orcid.org/0000-0001-6002-6980"},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernd Bischl","raw_affiliation_strings":["Ludwig-Maximilians-University, Munich, Germany","Ludwig-Maximilians-University Munich, Germany#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ludwig-Maximilians-University, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]},{"raw_affiliation_string":"Ludwig-Maximilians-University Munich, Germany#TAB#","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016794035","display_name":"Joaquin Vanschoren","orcid":"https://orcid.org/0000-0001-7044-9805"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Joaquin Vanschoren","raw_affiliation_strings":["University of Eindhoven, Eindhoven, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Eindhoven, Eindhoven, Netherlands","institution_ids":["https://openalex.org/I83019370"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1268,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.32005545,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9997000098228455,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9997000098228455,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9977999925613403,"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/hyperparameter","display_name":"Hyperparameter","score":0.8471676111221313},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.720927894115448},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6909667253494263},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6227322816848755},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5998525619506836},{"id":"https://openalex.org/keywords/symbolic-regression","display_name":"Symbolic regression","score":0.5258976817131042},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.48855385184288025},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.481806218624115},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"Genetic programming","score":0.42849239706993103},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.41324543952941895},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37888383865356445},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.09507668018341064}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.8471676111221313},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.720927894115448},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6909667253494263},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6227322816848755},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5998525619506836},{"id":"https://openalex.org/C2776400721","wikidata":"https://www.wikidata.org/wiki/Q18171762","display_name":"Symbolic regression","level":3,"score":0.5258976817131042},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.48855385184288025},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.481806218624115},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.42849239706993103},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41324543952941895},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37888383865356445},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.09507668018341064},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.1145/3449726.3459532","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3449726.3459532","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3449726.3459532&file=p151-gijsbers_suppl.pdf","source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2106.05767","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.05767","pdf_url":"https://arxiv.org/pdf/2106.05767","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":null,"raw_type":"text"},{"id":"pmh:oai:pure.tue.nl:openaire/ae881f8e-f2dd-45fc-8c94-4a31953cf337","is_oa":true,"landing_page_url":"https://research.tue.nl/en/publications/ae881f8e-f2dd-45fc-8c94-4a31953cf337","pdf_url":"https://pure.tue.nl/ws/files/360146640/3449726.3459532_1_.pdf","source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Gijsbers, P, Pfisterer, F, van Rijn, J N, Bischl, B & Vanschoren, J 2021, Meta-learning for symbolic hyperparameter defaults. in F Chicano (ed.), GECCO '21 : Proceedings of the Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, Inc., New York, pp. 151-152, 2021 Genetic and Evolutionary Computation Conference, GECCO 2021, Lille, France, 10/07/21. https://doi.org/10.1145/3449726.3459532","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"mag:3167936803","is_oa":true,"landing_page_url":"http://arxiv.org/pdf/2106.05767.pdf","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:scholarlypublications.universiteitleiden.nl:item_3277252","is_oa":false,"landing_page_url":"https://hdl.handle.net/1887/3277252","pdf_url":null,"source":{"id":"https://openalex.org/S4306400850","display_name":"Leiden Repository (Leiden University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I121797337","host_organization_name":"Leiden University","host_organization_lineage":["https://openalex.org/I121797337"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"GECCO '21: Proceedings of the genetic and evolutionary computation conference companion","raw_type":"Article in monograph or in proceedings"},{"id":"pmh:ul:oai:scholarlypublications.universiteitleiden.nl:item_3277252","is_oa":true,"landing_page_url":"http://hdl.handle.net/1887/3277252","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"GECCO '21: Proceedings of the genetic and evolutionary computation conference companion, 151 - 152. New York: ACM","raw_type":"info:eu-repo/semantics/article"},{"id":"doi:10.48550/arxiv.2106.05767","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2106.05767","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-journal"}],"best_oa_location":{"id":"doi:10.1145/3449726.3459532","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3449726.3459532","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3449726.3459532&file=p151-gijsbers_suppl.pdf","source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3467264548","display_name":null,"funder_award_id":"01IS18036A","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"}],"funders":[{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3167936803.pdf","grobid_xml":"https://content.openalex.org/works/W3167936803.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W60686164","https://openalex.org/W76331760","https://openalex.org/W116375701","https://openalex.org/W122178443","https://openalex.org/W1573980408","https://openalex.org/W1640798781","https://openalex.org/W2040492000","https://openalex.org/W2097360283","https://openalex.org/W2109042184","https://openalex.org/W2110990923","https://openalex.org/W2126105956","https://openalex.org/W2131241448","https://openalex.org/W2132862423","https://openalex.org/W2133990480","https://openalex.org/W2153635508","https://openalex.org/W2157966686","https://openalex.org/W2182070128","https://openalex.org/W2182361439","https://openalex.org/W2296218809","https://openalex.org/W2477400917","https://openalex.org/W2575220271","https://openalex.org/W2616207277","https://openalex.org/W2750387120","https://openalex.org/W2752331852","https://openalex.org/W2860358344","https://openalex.org/W2895399985","https://openalex.org/W2901752052","https://openalex.org/W2918998967","https://openalex.org/W2963248505","https://openalex.org/W2963469388","https://openalex.org/W2996717911","https://openalex.org/W3007385124","https://openalex.org/W3043188097","https://openalex.org/W3044836307","https://openalex.org/W3046876458","https://openalex.org/W3099934359","https://openalex.org/W3102027041","https://openalex.org/W3102476541"],"related_works":["https://openalex.org/W3180812695","https://openalex.org/W3195699808","https://openalex.org/W1663203009","https://openalex.org/W3112667379","https://openalex.org/W2164050144","https://openalex.org/W3124569606","https://openalex.org/W3177719755","https://openalex.org/W2980981830","https://openalex.org/W3210457622","https://openalex.org/W2990914544","https://openalex.org/W2198076614","https://openalex.org/W2949517868","https://openalex.org/W1610215495","https://openalex.org/W2997788840","https://openalex.org/W3082696595","https://openalex.org/W3200863653","https://openalex.org/W2397582304","https://openalex.org/W2073050283","https://openalex.org/W2962909570","https://openalex.org/W3128888385"],"abstract_inverted_index":{"Hyperparameter":[0],"optimization":[1,24,68],"in":[2,43],"machine":[3],"learning":[4,12,90],"(ML)":[5],"deals":[6],"with":[7],"the":[8,46,49,61,71],"problem":[9],"of":[10,45,48,60,89,96,103,114],"empirically":[11],"an":[13,87,117],"optimal":[14],"algorithm":[15],"configuration":[16,59],"from":[17,99],"data,":[18],"usually":[19,79],"formulated":[20],"as":[21,82,94,129,131],"a":[22,31,53,100,112],"black-box":[23],"problem.":[25],"In":[26,70],"this":[27],"work,":[28],"we":[29],"propose":[30,86],"zero-shot":[32],"method":[33,123,148],"to":[34,65],"meta-learn":[35],"symbolic":[36,73,92,152],"default":[37,76],"hyperparameter":[38,67],"configurations":[39,93],"that":[40,146],"are":[41],"expressed":[42],"terms":[44],"properties":[47,98],"dataset.":[50],"This":[51],"enables":[52],"much":[54],"faster,":[55],"but":[56],"still":[57],"data-dependent,":[58],"ML":[62,137],"algorithm,":[63],"compared":[64],"standard":[66],"approaches.":[69],"past,":[72],"and":[74,144],"static":[75],"values":[77],"have":[78],"been":[80],"obtained":[81],"hand-crafted":[83],"heuristics.":[84],"We":[85,120],"approach":[88],"such":[91],"formulas":[95],"dataset":[97],"large":[101],"set":[102],"prior":[104],"evaluations":[105],"on":[106,124,132,139],"multiple":[107],"datasets":[108,143],"by":[109],"optimizing":[110],"over":[111],"grammar":[113],"expressions":[115],"using":[116],"evolutionary":[118],"algorithm.":[119],"evaluate":[121],"our":[122,147],"surrogate":[125],"empirical":[126],"performance":[127],"models":[128],"well":[130],"real":[133],"data":[134],"across":[135],"6":[136],"algorithms":[138],"more":[140],"than":[141],"100":[142],"demonstrate":[145],"indeed":[149],"finds":[150],"viable":[151],"defaults.":[153]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}