{"id":"https://openalex.org/W2488432052","doi":"https://doi.org/10.1145/2908812.2908864","title":"Population Size Adaptation for the CMA-ES Based on the Estimation Accuracy of the Natural Gradient","display_name":"Population Size Adaptation for the CMA-ES Based on the Estimation Accuracy of the Natural Gradient","publication_year":2016,"publication_date":"2016-07-20","ids":{"openalex":"https://openalex.org/W2488432052","doi":"https://doi.org/10.1145/2908812.2908864","mag":"2488432052"},"language":"en","primary_location":{"id":"doi:10.1145/2908812.2908864","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2908812.2908864","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference 2016","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kouhei Nishida","orcid":null},"institutions":[{"id":"https://openalex.org/I135822937","display_name":"Hanoi National University of Education","ror":"https://ror.org/0360g3z42","country_code":"VN","type":"education","lineage":["https://openalex.org/I135822937"]},{"id":"https://openalex.org/I137975476","display_name":"Shinshu University","ror":"https://ror.org/0244rem06","country_code":"JP","type":"education","lineage":["https://openalex.org/I137975476"]}],"countries":["JP","VN"],"is_corresponding":false,"raw_author_name":"Kouhei Nishida","raw_affiliation_strings":["Shinshu University, Nagano, Japan","Hanoi National University of Education"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shinshu University, Nagano, Japan","institution_ids":["https://openalex.org/I137975476"]},{"raw_affiliation_string":"Hanoi National University of Education","institution_ids":["https://openalex.org/I135822937"]}]},{"author_position":"last","author":{"id":null,"display_name":"Youhei Akimoto","orcid":null},"institutions":[{"id":"https://openalex.org/I137975476","display_name":"Shinshu University","ror":"https://ror.org/0244rem06","country_code":"JP","type":"education","lineage":["https://openalex.org/I137975476"]},{"id":"https://openalex.org/I142476485","display_name":"\u00c9cole Polytechnique","ror":"https://ror.org/05hy3tk52","country_code":"FR","type":"education","lineage":["https://openalex.org/I142476485","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I4210107641","display_name":"Centre de Math\u00e9matiques Appliqu\u00e9es de l'\u00c9cole polytechnique","ror":"https://ror.org/012e1xn46","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I142476485","https://openalex.org/I4210107641","https://openalex.org/I4210141950","https://openalex.org/I4210145102"]}],"countries":["FR","JP"],"is_corresponding":false,"raw_author_name":"Youhei Akimoto","raw_affiliation_strings":["Shinshu University, Nagano, Japan","Centre de Math\u00e9matiques Appliqu\u00e9es - Ecole Polytechnique","Randomized Optimisation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shinshu University, Nagano, Japan","institution_ids":["https://openalex.org/I137975476"]},{"raw_affiliation_string":"Centre de Math\u00e9matiques Appliqu\u00e9es - Ecole Polytechnique","institution_ids":["https://openalex.org/I142476485","https://openalex.org/I4210107641"]},{"raw_affiliation_string":"Randomized Optimisation","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9804,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.88414873,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"237","last_page":"244"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9945999979972839,"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/T10057","display_name":"Face and Expression Recognition","score":0.9914000034332275,"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/cma-es","display_name":"CMA-ES","score":0.8551477193832397},{"id":"https://openalex.org/keywords/evolution-strategy","display_name":"Evolution strategy","score":0.6427378058433533},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.6144073009490967},{"id":"https://openalex.org/keywords/population-size","display_name":"Population size","score":0.5616682171821594},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5248429775238037},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4960702359676361},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.484507292509079},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.47831419110298157},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4721370339393616},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4471309185028076},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.432206392288208},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4294852316379547},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3713465631008148},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.35339659452438354},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.2156619131565094}],"concepts":[{"id":"https://openalex.org/C205555498","wikidata":"https://www.wikidata.org/wiki/Q505588","display_name":"CMA-ES","level":4,"score":0.8551477193832397},{"id":"https://openalex.org/C207002847","wikidata":"https://www.wikidata.org/wiki/Q2912857","display_name":"Evolution strategy","level":3,"score":0.6427378058433533},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.6144073009490967},{"id":"https://openalex.org/C169733012","wikidata":"https://www.wikidata.org/wiki/Q1613416","display_name":"Population size","level":3,"score":0.5616682171821594},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5248429775238037},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4960702359676361},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.484507292509079},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.47831419110298157},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4721370339393616},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4471309185028076},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.432206392288208},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4294852316379547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3713465631008148},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35339659452438354},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.2156619131565094},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2908812.2908864","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2908812.2908864","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference 2016","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-01591423v1","is_oa":false,"landing_page_url":"https://inria.hal.science/hal-01591423","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 2017 Genetic and Evolutionary Computation Conference Companion (GECCO '17 Companion), Jul 2017, Berlin, Germany. pp.1756 - 1763, ⟨10.1145/2908812.2908864⟩","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G3596747759","display_name":"Automatic Design of Efficient Algorithms for Black-Box Optimization in Arbitrary Search Domains","funder_award_id":"15K16063","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320315724","display_name":"Kayamori Foundation of Informational Science Advancement","ror":null},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W7934506","https://openalex.org/W1479971399","https://openalex.org/W1480347379","https://openalex.org/W1503296932","https://openalex.org/W1605438009","https://openalex.org/W1970789124","https://openalex.org/W2034813183","https://openalex.org/W2097263684","https://openalex.org/W2104578628","https://openalex.org/W2112036188","https://openalex.org/W2138537392","https://openalex.org/W2156106639"],"related_works":["https://openalex.org/W1492325323","https://openalex.org/W1579744901","https://openalex.org/W2510724351","https://openalex.org/W3087341323","https://openalex.org/W2465356436","https://openalex.org/W2552260697","https://openalex.org/W3119219900","https://openalex.org/W2926551842","https://openalex.org/W2022594112","https://openalex.org/W4211082860"],"abstract_inverted_index":{"We":[0,54,69],"propose":[1,70],"a":[2,56,71,99,109,126],"novel":[3,72],"strategy":[4,26,29,73,86,139],"to":[5,74,80,105,107],"adapt":[6,75],"the":[7,11,19,33,36,41,47,51,59,62,66,76,81,116,119,122,135,141],"population":[8,77,101,123,128],"size,":[9],"i.e.":[10],"number":[12],"of":[13,35,50,58,61,65,118,121],"candidate":[14],"solutions":[15],"per":[16],"iteration,":[17],"for":[18,140],"rank-mu":[20,37],"update":[21,38],"covariance":[22],"matrix":[23],"adaptation":[24,120],"evolution":[25],"(CMA-ES).":[27],"Our":[28],"is":[30,87,103,131],"based":[31],"on":[32,46,89,145],"interpretation":[34],"CMA-ES":[39],"as":[40],"stochastic":[42],"natural":[43,67],"gradient":[44],"approach":[45],"parameter":[48],"space":[49],"sampling":[52],"distribution.":[53],"introduce":[55],"measurement":[57],"accuracy":[60,82],"current":[63],"estimate":[64],"gradient.":[68],"size":[78,102,124],"according":[79],"measure.":[83],"The":[84,112],"proposed":[85],"evaluated":[88],"test":[90,147],"functions":[91,94,97],"including":[92],"rugged":[93],"and":[95],"noisy":[96,146],"where":[98],"larger":[100],"known":[104],"help":[106],"find":[108],"better":[110],"solution.":[111],"experimental":[113],"results":[114],"show":[115],"advantage":[117],"over":[125],"fixed":[127],"size.":[129],"It":[130],"also":[132],"compared":[133],"with":[134],"state-of-the-art":[136],"uncertainty":[137],"handling":[138],"CMA-ES,":[142],"namely":[143],"UH-CMA-ES,":[144],"functions.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2016-08-23T00:00:00"}