{"id":"https://openalex.org/W6911239952","doi":"https://doi.org/10.5281/zenodo.10911264","title":"Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization -- Reproducibility Files","display_name":"Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization -- Reproducibility Files","publication_year":2024,"publication_date":"2024-04-03","ids":{"openalex":"https://openalex.org/W6911239952","doi":"https://doi.org/10.5281/zenodo.10911264"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.10911264","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.10911264","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.10911264","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Dietrich, Konstantin","orcid":"https://orcid.org/0000-0002-5383-7475"},"institutions":[{"id":"https://openalex.org/I4401726909","display_name":"Center for Scalable Data Analytics and Artificial Intelligence","ror":"https://ror.org/01t4ttr56","country_code":"DE","type":"education","lineage":["https://openalex.org/I4401726909","https://openalex.org/I78650965","https://openalex.org/I926574661"]},{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dietrich, Konstantin","raw_affiliation_strings":["ScaDS.AI","TU Dresden"],"raw_orcid":"https://orcid.org/0000-0002-5383-7475","affiliations":[{"raw_affiliation_string":"ScaDS.AI","institution_ids":["https://openalex.org/I4401726909"]},{"raw_affiliation_string":"TU Dresden","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Vermetten, Diederick","orcid":"https://orcid.org/0000-0003-3040-7162"},"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":"Vermetten, Diederick","raw_affiliation_strings":["Leiden University"],"raw_orcid":"https://orcid.org/0000-0003-3040-7162","affiliations":[{"raw_affiliation_string":"Leiden University","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Doerr, Carola","orcid":"https://orcid.org/0000-0002-4981-3227"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Doerr, Carola","raw_affiliation_strings":["French National Centre for Scientific Research","Sorbonne University"],"raw_orcid":"https://orcid.org/0000-0002-4981-3227","affiliations":[{"raw_affiliation_string":"French National Centre for Scientific Research","institution_ids":["https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Sorbonne University","institution_ids":["https://openalex.org/I39804081"]}]},{"author_position":"last","author":{"id":null,"display_name":"Kerschke, Pascal","orcid":"https://orcid.org/0000-0003-2862-1418"},"institutions":[{"id":"https://openalex.org/I4401726909","display_name":"Center for Scalable Data Analytics and Artificial Intelligence","ror":"https://ror.org/01t4ttr56","country_code":"DE","type":"education","lineage":["https://openalex.org/I4401726909","https://openalex.org/I78650965","https://openalex.org/I926574661"]},{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kerschke, Pascal","raw_affiliation_strings":["ScaDS.AI","TU Dresden"],"raw_orcid":"https://orcid.org/0000-0003-2862-1418","affiliations":[{"raw_affiliation_string":"ScaDS.AI","institution_ids":["https://openalex.org/I4401726909"]},{"raw_affiliation_string":"TU Dresden","institution_ids":["https://openalex.org/I78650965"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6126999855041504},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5530999898910522},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.546500027179718},{"id":"https://openalex.org/keywords/data-file","display_name":"Data file","score":0.5300999879837036},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.48570001125335693},{"id":"https://openalex.org/keywords/scripting-language","display_name":"Scripting language","score":0.4458000063896179},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.43059998750686646},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4133000075817108},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.37279999256134033}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7996000051498413},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6126999855041504},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5530999898910522},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.546500027179718},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5446000099182129},{"id":"https://openalex.org/C171730128","wikidata":"https://www.wikidata.org/wiki/Q5227290","display_name":"Data file","level":2,"score":0.5300999879837036},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.48570001125335693},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.4458000063896179},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.43059998750686646},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3995000123977661},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.37279999256134033},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.35420000553131104},{"id":"https://openalex.org/C9893847","wikidata":"https://www.wikidata.org/wiki/Q1425625","display_name":"Reproducibility","level":2,"score":0.34689998626708984},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.34060001373291016},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.33410000801086426},{"id":"https://openalex.org/C96147967","wikidata":"https://www.wikidata.org/wiki/Q190686","display_name":"Subroutine","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.314300000667572},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.251800000667572},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.2515999972820282},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5281/zenodo.10911264","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.10911264","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"dataset"}],"best_oa_location":{"id":"doi:10.5281/zenodo.10911264","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.10911264","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,213],"repository":[1],"contains":[2],"the":[3,7,10,36,41,50,55,59,61,82,88,112,127,133,139,167,187,201,206,210,225,240,244],"files":[4,32,98,182],"to":[5,34,53],"reproduce":[6],"results":[8,128,214],"from":[9,239],"paper":[11],"\"Impact":[12],"of":[13,43,84,129,250],"Training":[14],"Instance":[15],"Selection":[16,20],"on":[17],"Automated":[18],"Algorithm":[19],"Models":[21],"for":[22,40,74,90,166,222],"Numerical":[23],"Black-box":[24],"Optimization\".":[25],"Data":[26,174],"Collection":[27],"In":[28],"this":[29,80,100,124,191],"folder,":[30,81],"all":[31,77,236],"used":[33,52,73,246,257],"generate":[35,54],"raw":[37],"performance":[38,114],"data":[39,104,115,159,207],"set":[42,107],"algorithms":[44],"are":[45,68,136,193,219],"included,":[46],"as":[47,49,95,155,162,264],"well":[48],"code":[51],"ELA":[56,158],"features.":[57],"For":[58,76],"performance,":[60],"packages":[62],"'ioh',":[63],"'nevergrad',":[64],"'modde'":[65],"and":[66,87,102,164,170,177,235],"'modcma'":[67],"essential,":[69],"while":[70],"'pflacco'":[71],"is":[72,120,160,262],"ELA.":[75],"scripts":[78],"in":[79,99,123,138,186,200,209,215],"number":[83],"parallel":[85],"threads":[86],"folders":[89],"reading":[91],"function":[92],"settings":[93],"(included":[94],"3":[96],"csv":[97],"folder)":[101],"storing":[103],"should":[105],"be":[106,184,256],"before":[108],"execution.":[109],"Note":[110],"that":[111],"full":[113],"exceeds":[116],"50GB,":[117],"so":[118],"it":[119,131],"not":[121],"included":[122,137,154,161,221,237],"repository.":[125],"Instead,":[126],"processing":[130],"(using":[132],"aocc_extraction":[134],"script)":[135],"'auc_MABBOB'":[140],"folder":[141,192],"(spread":[142],"across":[143],"multiple":[144],"csv-files,":[145,217],"with":[146,204,229,258],"a":[147,150,253],"version":[148],"using":[149],"different":[151],"budget":[152],"factor":[153],"well).":[156],"The":[157,179],"'ELA'":[163],"'ELA_BBOB'":[165],"affine":[168],"combinations":[169],"component":[171],"functions":[172],"respectively.":[173],"Processing,":[175],"Analysis":[176],"Visualization":[178],"remaining":[180,226],"reproducibility":[181],"can":[183],"found":[185],"Reproducibility":[188],"folder.":[189],"Within":[190],"several":[194],"notebooks":[195,227],"which":[196,218],"handle":[197],"various":[198],"steps":[199],"pipeline,":[202],"starting":[203],"preprocessing":[205],"collected":[208],"previous":[211],"steps.":[212],"some":[216],"also":[220],"convenience.":[223],"Afterwards,":[224],"deal":[228],"correlation":[230],"analysis,":[231],"instance":[232],"selection":[233],"methods,":[234],"plots":[238],"paper.":[241],"To":[242],"match":[243],"environment":[245],"during":[247],"our":[248],"execution":[249],"these":[251],"scripts.":[252],"yml-file":[254],"(to":[255],"conda":[259],"or":[260],"mamba)":[261],"available":[263],"well.":[265]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
