{"id":"https://openalex.org/W2968375771","doi":"https://doi.org/10.1109/cec.2019.8790149","title":"An Efficient Elitist Covariance Matrix Adaptation for Continuous Local Search in High Dimension","display_name":"An Efficient Elitist Covariance Matrix Adaptation for Continuous Local Search in High Dimension","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2968375771","doi":"https://doi.org/10.1109/cec.2019.8790149","mag":"2968375771"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2019.8790149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2019.8790149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Congress on Evolutionary Computation (CEC)","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":"https://openalex.org/A5100357915","display_name":"Zhenhua Li","orcid":"https://orcid.org/0000-0001-5099-1795"},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Zhenhua Li","raw_affiliation_strings":["Institute of Computer Graphics and Vision, Graz University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Graphics and Vision, Graz University of Technology","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071098819","display_name":"Jingda Deng","orcid":"https://orcid.org/0000-0002-3347-745X"},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Jingda Deng","raw_affiliation_strings":["Institute of Computer Graphics and Vision, Graz University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Graphics and Vision, Graz University of Technology","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047167952","display_name":"Weifeng Gao","orcid":"https://orcid.org/0000-0003-3853-0771"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weifeng Gao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000546219","display_name":"Qingfu Zhang","orcid":"https://orcid.org/0000-0003-0786-0671"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qingfu Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100610638","display_name":"Hai\u2010Lin Liu","orcid":"https://orcid.org/0000-0003-2276-1938"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hai-Lin Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.328,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.6012861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"15","issue":null,"first_page":"936","last_page":"943"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9976000189781189,"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":0.9976000189781189,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9927999973297119,"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"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9887999892234802,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cma-es","display_name":"CMA-ES","score":0.8772488832473755},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.7507392764091492},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6546401381492615},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.6104546189308167},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5119968056678772},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5010311603546143},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.49232280254364014},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37619447708129883},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3104820251464844},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.2832223176956177},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08082807064056396},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06217154860496521}],"concepts":[{"id":"https://openalex.org/C205555498","wikidata":"https://www.wikidata.org/wiki/Q505588","display_name":"CMA-ES","level":4,"score":0.8772488832473755},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.7507392764091492},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6546401381492615},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.6104546189308167},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5119968056678772},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5010311603546143},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.49232280254364014},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37619447708129883},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3104820251464844},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.2832223176956177},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08082807064056396},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06217154860496521},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2019.8790149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2019.8790149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W7934506","https://openalex.org/W102487131","https://openalex.org/W1480347379","https://openalex.org/W1492325323","https://openalex.org/W1567473651","https://openalex.org/W1576660662","https://openalex.org/W1971514372","https://openalex.org/W2003066178","https://openalex.org/W2024372894","https://openalex.org/W2034813183","https://openalex.org/W2050079439","https://openalex.org/W2104604585","https://openalex.org/W2112036188","https://openalex.org/W2116990014","https://openalex.org/W2140671219","https://openalex.org/W2143381319","https://openalex.org/W2151965738","https://openalex.org/W2168924884","https://openalex.org/W2509569228","https://openalex.org/W2549617326","https://openalex.org/W2728489159","https://openalex.org/W2766293931","https://openalex.org/W2901412188","https://openalex.org/W2962757795","https://openalex.org/W3007384386","https://openalex.org/W6628707872","https://openalex.org/W6682262322","https://openalex.org/W6729329756","https://openalex.org/W6740800178"],"related_works":["https://openalex.org/W2926551842","https://openalex.org/W3119219900","https://openalex.org/W2022594112","https://openalex.org/W2572601863","https://openalex.org/W3112846993","https://openalex.org/W4211082860","https://openalex.org/W2056742037","https://openalex.org/W2587300415","https://openalex.org/W4303684144","https://openalex.org/W1976318097"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,28,33,87,101],"computationally":[6],"efficient":[7],"variant":[8],"of":[9,36,48,89,103],"elitist":[10],"covariance":[11],"matrix":[12],"evolution":[13],"strategy":[14],"for":[15],"continuous":[16],"local":[17],"search":[18,38],"in":[19,27],"high":[20,58],"dimensional":[21,59],"space.":[22],"It":[23],"focuses":[24],"on":[25,100],"searching":[26],"low-dimensional":[29],"subspace":[30],"expanded":[31],"by":[32,86],"small":[34],"number":[35],"promising":[37],"directions.":[39],"This":[40],"leads":[41],"to":[42,55,57,65,98],"the":[43,53,67,71,79,83],"linear":[44],"internal":[45],"computational":[46],"complexity":[47],"each":[49],"iteration,":[50],"which":[51],"enables":[52],"algorithm":[54,81],"scale":[56],"problems.":[60],"We":[61],"conduct":[62],"comprehensive":[63],"experiments":[64],"evaluate":[66],"parameter":[68],"sensitivity":[69],"and":[70,91],"algorithm\u2019s":[72],"performance.":[73],"The":[74],"experimental":[75],"results":[76],"validate":[77],"that":[78],"proposed":[80],"reduces":[82],"running":[84],"time":[85],"factor":[88],"ten,":[90],"it":[92],"can":[93],"be":[94],"easily":[95],"scaled":[96],"up":[97],"n>1000":[99],"set":[102],"commonly":[104],"used":[105],"test":[106],"functions.":[107]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
