{"id":"https://openalex.org/W2950434885","doi":"https://doi.org/10.1007/s10710-019-09357-1","title":"A covariance matrix adaptation evolution strategy in reproducing kernel Hilbert space","display_name":"A covariance matrix adaptation evolution strategy in reproducing kernel Hilbert space","publication_year":2019,"publication_date":"2019-06-19","ids":{"openalex":"https://openalex.org/W2950434885","doi":"https://doi.org/10.1007/s10710-019-09357-1","mag":"2950434885"},"language":"en","primary_location":{"id":"doi:10.1007/s10710-019-09357-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10710-019-09357-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10710-019-09357-1.pdf","source":{"id":"https://openalex.org/S47930974","display_name":"Genetic Programming and Evolvable Machines","issn_l":"1389-2576","issn":["1389-2576","1573-7632"],"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":"Genetic Programming and Evolvable Machines","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/s10710-019-09357-1.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020334464","display_name":"Viet-Hung Dang","orcid":null},"institutions":[{"id":"https://openalex.org/I170238339","display_name":"Duy Tan University","ror":"https://ror.org/05ezss144","country_code":"VN","type":"education","lineage":["https://openalex.org/I170238339"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Viet-Hung Dang","raw_affiliation_strings":["Department of Computer Science, Duy Tan University, Da Nang, Vietnam"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Duy Tan University, Da Nang, Vietnam","institution_ids":["https://openalex.org/I170238339"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043775193","display_name":"Ngo Anh Vien","orcid":"https://orcid.org/0000-0001-9646-267X"},"institutions":[{"id":"https://openalex.org/I126231945","display_name":"Queen's University Belfast","ror":"https://ror.org/00hswnk62","country_code":"GB","type":"education","lineage":["https://openalex.org/I126231945"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ngo Anh Vien","raw_affiliation_strings":["School of EEECS, Queen\u2019s University Belfast, Belfast, UK"],"affiliations":[{"raw_affiliation_string":"School of EEECS, Queen\u2019s University Belfast, Belfast, UK","institution_ids":["https://openalex.org/I126231945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112330829","display_name":"TaeChoong Chung","orcid":null},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"TaeChoong Chung","raw_affiliation_strings":["Department of Computer Engineering, Kyung Hee University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Kyung Hee University, Seoul, Korea","institution_ids":["https://openalex.org/I35928602"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043775193"],"corresponding_institution_ids":["https://openalex.org/I126231945"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":1.0116,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.8258934,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"20","issue":"4","first_page":"479","last_page":"501"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9979000091552734,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9979000091552734,"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/T12676","display_name":"Machine Learning and ELM","score":0.9962999820709229,"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/T10320","display_name":"Neural Networks and Applications","score":0.9955999851226807,"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/reproducing-kernel-hilbert-space","display_name":"Reproducing kernel Hilbert space","score":0.9030781388282776},{"id":"https://openalex.org/keywords/cma-es","display_name":"CMA-ES","score":0.7487916946411133},{"id":"https://openalex.org/keywords/representer-theorem","display_name":"Representer theorem","score":0.5634908080101013},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5522230267524719},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5183478593826294},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49274519085884094},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.46838313341140747},{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.45475780963897705},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.44559502601623535},{"id":"https://openalex.org/keywords/covariance-function","display_name":"Covariance function","score":0.43690240383148193},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43097764253616333},{"id":"https://openalex.org/keywords/hilbert-space","display_name":"Hilbert space","score":0.39853423833847046},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3463331460952759},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.30312347412109375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29559874534606934},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.2899003028869629},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.13213592767715454},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.07879126071929932}],"concepts":[{"id":"https://openalex.org/C80884492","wikidata":"https://www.wikidata.org/wiki/Q3345678","display_name":"Reproducing kernel Hilbert space","level":3,"score":0.9030781388282776},{"id":"https://openalex.org/C205555498","wikidata":"https://www.wikidata.org/wiki/Q505588","display_name":"CMA-ES","level":4,"score":0.7487916946411133},{"id":"https://openalex.org/C172623408","wikidata":"https://www.wikidata.org/wiki/Q7314263","display_name":"Representer theorem","level":5,"score":0.5634908080101013},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5522230267524719},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5183478593826294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49274519085884094},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.46838313341140747},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.45475780963897705},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.44559502601623535},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.43690240383148193},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43097764253616333},{"id":"https://openalex.org/C62799726","wikidata":"https://www.wikidata.org/wiki/Q190056","display_name":"Hilbert space","level":2,"score":0.39853423833847046},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3463331460952759},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.30312347412109375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29559874534606934},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.2899003028869629},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.13213592767715454},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.07879126071929932},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10710-019-09357-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10710-019-09357-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10710-019-09357-1.pdf","source":{"id":"https://openalex.org/S47930974","display_name":"Genetic Programming and Evolvable Machines","issn_l":"1389-2576","issn":["1389-2576","1573-7632"],"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":"Genetic Programming and Evolvable Machines","raw_type":"journal-article"},{"id":"pmh:oai:pure.qub.ac.uk/portal:publications/616d740b-cdf5-4766-b03c-4ce33b0b43bd","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/616d740b-cdf5-4766-b03c-4ce33b0b43bd","pdf_url":null,"source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Dang, V H, Vien, N A & Chung, T C 2019, 'A covariance matrix adaptation evolution strategy in reproducing kernel Hilbert space', Genetic Programming and Evolvable Machines, pp. 1-23. https://doi.org/10.1007/s10710-019-09357-1","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1007/s10710-019-09357-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10710-019-09357-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10710-019-09357-1.pdf","source":{"id":"https://openalex.org/S47930974","display_name":"Genetic Programming and Evolvable Machines","issn_l":"1389-2576","issn":["1389-2576","1573-7632"],"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":"Genetic Programming and Evolvable Machines","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1995273408","display_name":null,"funder_award_id":"2016.18","funder_id":"https://openalex.org/F4320309617","funder_display_name":"National Foundation for Science and Technology Development"},{"id":"https://openalex.org/G2905686298","display_name":null,"funder_award_id":"NRF-2017R1D1A1B04036354","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G4900121520","display_name":null,"funder_award_id":"NRF-2017R1D1A1B","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G7110693004","display_name":null,"funder_award_id":"102.05","funder_id":"https://openalex.org/F4320309617","funder_display_name":"National Foundation for Science and Technology Development"},{"id":"https://openalex.org/G982292920","display_name":null,"funder_award_id":"NRF-20","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320309617","display_name":"National Foundation for Science and Technology Development","ror":"https://ror.org/04rw64z44"},{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321332","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2950434885.pdf","grobid_xml":"https://content.openalex.org/works/W2950434885.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W7934506","https://openalex.org/W215298514","https://openalex.org/W314779054","https://openalex.org/W757502775","https://openalex.org/W1262227701","https://openalex.org/W1502364872","https://openalex.org/W1559005923","https://openalex.org/W1560724230","https://openalex.org/W1577352482","https://openalex.org/W1587559447","https://openalex.org/W1746819321","https://openalex.org/W1869302287","https://openalex.org/W1993309788","https://openalex.org/W2009618608","https://openalex.org/W2012587148","https://openalex.org/W2022806724","https://openalex.org/W2046727971","https://openalex.org/W2059654640","https://openalex.org/W2063741856","https://openalex.org/W2066251678","https://openalex.org/W2098524868","https://openalex.org/W2104759087","https://openalex.org/W2107221565","https://openalex.org/W2115003579","https://openalex.org/W2118556122","https://openalex.org/W2119567691","https://openalex.org/W2119717200","https://openalex.org/W2121863487","https://openalex.org/W2129809168","https://openalex.org/W2131222273","https://openalex.org/W2133220762","https://openalex.org/W2138537392","https://openalex.org/W2141735805","https://openalex.org/W2151965738","https://openalex.org/W2155027007","https://openalex.org/W2163302320","https://openalex.org/W2172968643","https://openalex.org/W2234882433","https://openalex.org/W2235234948","https://openalex.org/W2275728380","https://openalex.org/W2336687883","https://openalex.org/W2412669390","https://openalex.org/W2415155889","https://openalex.org/W2561675875","https://openalex.org/W2578657880","https://openalex.org/W2579190672","https://openalex.org/W2762002200","https://openalex.org/W2802349643","https://openalex.org/W2983836991","https://openalex.org/W4211049957","https://openalex.org/W4214717370","https://openalex.org/W4241335442","https://openalex.org/W4293259004","https://openalex.org/W6602641256","https://openalex.org/W6603932791","https://openalex.org/W6605121509","https://openalex.org/W6631700454","https://openalex.org/W6632351690","https://openalex.org/W6653548176"],"related_works":["https://openalex.org/W2061713275","https://openalex.org/W1994655188","https://openalex.org/W598858589","https://openalex.org/W4243330733","https://openalex.org/W2591253179","https://openalex.org/W2539736905","https://openalex.org/W2172290429","https://openalex.org/W3123393116","https://openalex.org/W3217442333","https://openalex.org/W1744346525"],"abstract_inverted_index":{"The":[0],"covariance":[1,152,164],"matrix":[2],"adaptation":[3],"evolution":[4],"strategy":[5],"(CMA-ES)":[6],"is":[7,99,121,143,214],"an":[8,197],"efficient":[9,170],"derivative-free":[10],"optimization":[11,81,219],"algorithm.":[12],"It":[13],"optimizes":[14],"a":[15,20,59,93,100,108,116,140,211],"black-box":[16,80,126,192],"objective":[17],"function":[18,51,64,102,111,136,150,161],"over":[19],"well-defined":[21],"parameter":[22],"space":[23,103],"in":[24,79,83,107,129,172,200,203,210],"which":[25,204],"feature":[26],"functions":[27,209],"are":[28,206],"often":[29],"defined":[30],"manually.":[31],"Therefore,":[32],"the":[33,41,44,48,76,159,163,173],"performance":[34],"of":[35,43,158,177],"those":[36],"techniques":[37],"strongly":[38],"depends":[39],"on":[40,58,134,216],"quality":[42],"chosen":[45],"features":[46],"or":[47],"underlying":[49],"parametric":[50],"space.":[52],"Hence,":[53],"enabling":[54],"CMA-ES":[55,118],"to":[56,92,123,181,188,194],"optimize":[57],"more":[60],"complex":[61],"and":[62,151,155,162,175,221],"general":[63],"class":[65],"has":[66],"long":[67],"been":[68],"desired.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73],"consider":[74],"modeling":[75,90],"input":[77],"spaces":[78,87],"non-parametrically":[82],"reproducing":[84],"kernel":[85],"Hilbert":[86],"(RKHS).":[88],"This":[89],"leads":[91],"functional":[94,127,218],"optimisation":[95,106,128],"problem":[96],"whose":[97],"domain":[98],"RKHS":[101],"that":[104,120],"enables":[105],"very":[109],"rich":[110],"class.":[112],"We":[113,183],"propose":[114],"CMA-ES-RKHS,":[115],"generalized":[117],"framework":[119,193],"able":[122],"carry":[124],"out":[125],"RKHS.":[130,212],"A":[131],"search":[132,195],"distribution":[133],"non-parametric":[135],"spaces,":[137],"represented":[138,207],"as":[139,208],"Gaussian":[141],"process,":[142],"adapted":[144],"by":[145,179],"updating":[146],"both":[147],"its":[148],"mean":[149,160],"operator.":[153],"Adaptive":[154],"sparse":[156],"representation":[157],"operator":[165],"can":[166],"be":[167],"retained":[168],"for":[169,196],"computation":[171],"updates":[174],"evaluations":[176],"CMA-ES-RKHS":[178,213],"resorting":[180],"sparsification.":[182],"will":[184],"also":[185],"show":[186],"how":[187],"apply":[189],"our":[190],"new":[191],"optimum":[198],"policy":[199],"reinforcement":[201,224],"learning":[202,225],"policies":[205],"evaluated":[215],"two":[217,222],"problems":[220],"bench-marking":[223],"domains.":[226]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
