{"id":"https://openalex.org/W4385190110","doi":"https://doi.org/10.1145/3583133.3596374","title":"A New Acquisition Function for Multi-objective Bayesian Optimization: Correlated Probability of Improvement","display_name":"A New Acquisition Function for Multi-objective Bayesian Optimization: Correlated Probability of Improvement","publication_year":2023,"publication_date":"2023-07-15","ids":{"openalex":"https://openalex.org/W4385190110","doi":"https://doi.org/10.1145/3583133.3596374"},"language":"en","primary_location":{"id":"doi:10.1145/3583133.3596374","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1145/3583133.3596374","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583133.3596374","source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3583133.3596374","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077564991","display_name":"Kaifeng Yang","orcid":"https://orcid.org/0000-0002-3353-3298"},"institutions":[{"id":"https://openalex.org/I4210126338","display_name":"Software Competence Center Hagenberg (Austria)","ror":"https://ror.org/02ks3nr96","country_code":"AT","type":"company","lineage":["https://openalex.org/I4210126338"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Kaifeng Yang","raw_affiliation_strings":["FH Hagenberg, Hagengerg, Austria"],"affiliations":[{"raw_affiliation_string":"FH Hagenberg, Hagengerg, Austria","institution_ids":["https://openalex.org/I4210126338"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100437965","display_name":"Kai Chen","orcid":"https://orcid.org/0000-0002-4081-0687"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Chen","raw_affiliation_strings":["Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013367027","display_name":"Michael Affenzeller","orcid":"https://orcid.org/0000-0001-5692-5940"},"institutions":[{"id":"https://openalex.org/I4210126338","display_name":"Software Competence Center Hagenberg (Austria)","ror":"https://ror.org/02ks3nr96","country_code":"AT","type":"company","lineage":["https://openalex.org/I4210126338"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Michael Affenzeller","raw_affiliation_strings":["FH Hagenberg, Hagenberg, Austria"],"affiliations":[{"raw_affiliation_string":"FH Hagenberg, Hagenberg, Austria","institution_ids":["https://openalex.org/I4210126338"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036623404","display_name":"Bernhard Werth","orcid":"https://orcid.org/0000-0002-7830-3138"},"institutions":[{"id":"https://openalex.org/I4210126338","display_name":"Software Competence Center Hagenberg (Austria)","ror":"https://ror.org/02ks3nr96","country_code":"AT","type":"company","lineage":["https://openalex.org/I4210126338"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Bernhard Werth","raw_affiliation_strings":["FH Hagenberg, Hagenberg, Austria"],"affiliations":[{"raw_affiliation_string":"FH Hagenberg, Hagenberg, Austria","institution_ids":["https://openalex.org/I4210126338"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5077564991"],"corresponding_institution_ids":["https://openalex.org/I4210126338"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15008796,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":null,"first_page":"2308","last_page":"2317"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":1.0,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9947999715805054,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.901236355304718},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6564406156539917},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6015793681144714},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5768306255340576},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5668579339981079},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.511776864528656},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.44622841477394104},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43215981125831604},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.4248208999633789},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3459334373474121},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30656659603118896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2549494802951813},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21850547194480896},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06929776072502136}],"concepts":[{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.901236355304718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6564406156539917},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6015793681144714},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5768306255340576},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5668579339981079},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.511776864528656},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.44622841477394104},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43215981125831604},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4248208999633789},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3459334373474121},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30656659603118896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2549494802951813},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21850547194480896},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06929776072502136},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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":1,"locations":[{"id":"doi:10.1145/3583133.3596374","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1145/3583133.3596374","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583133.3596374","source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3583133.3596374","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1145/3583133.3596374","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583133.3596374","source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1477544716","display_name":null,"funder_award_id":"Guangdong","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2972878393","display_name":null,"funder_award_id":"2022B1212010001","funder_id":"https://openalex.org/F4320322942","funder_display_name":"Chinese University of Hong Kong"},{"id":"https://openalex.org/G2981938667","display_name":null,"funder_award_id":"Shenzhen","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3718769366","display_name":null,"funder_award_id":"Shenzhen","funder_id":"https://openalex.org/F4320322942","funder_display_name":"Chinese University of Hong Kong"},{"id":"https://openalex.org/G37568934","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4941433343","display_name":"Probing the electric neutrality of the neutron","funder_award_id":"I 531","funder_id":"https://openalex.org/F4320321181","funder_display_name":"Austrian Science Fund"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6258415954","display_name":null,"funder_award_id":"Chinese","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G711740527","display_name":null,"funder_award_id":"I 5315","funder_id":"https://openalex.org/F4320321181","funder_display_name":"Austrian Science Fund"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321181","display_name":"Austrian Science Fund","ror":"https://ror.org/013tf3c58"},{"id":"https://openalex.org/F4320321514","display_name":"Central South University","ror":"https://ror.org/00f1zfq44"},{"id":"https://openalex.org/F4320322942","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385190110.pdf","grobid_xml":"https://content.openalex.org/works/W4385190110.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1510052597","https://openalex.org/W1529817821","https://openalex.org/W1539598433","https://openalex.org/W1891298814","https://openalex.org/W1969682141","https://openalex.org/W1975971707","https://openalex.org/W2008756354","https://openalex.org/W2059980448","https://openalex.org/W2065859486","https://openalex.org/W2071818961","https://openalex.org/W2097263684","https://openalex.org/W2098907614","https://openalex.org/W2105245738","https://openalex.org/W2106334424","https://openalex.org/W2111526171","https://openalex.org/W2136918060","https://openalex.org/W2138309709","https://openalex.org/W2149563116","https://openalex.org/W2151238122","https://openalex.org/W2151263643","https://openalex.org/W2288838258","https://openalex.org/W2533997953","https://openalex.org/W2540189295","https://openalex.org/W2548304608","https://openalex.org/W2559173494","https://openalex.org/W2728011051","https://openalex.org/W2763090371","https://openalex.org/W2802235618","https://openalex.org/W2885225402","https://openalex.org/W2885933134","https://openalex.org/W2894522179","https://openalex.org/W2896482837","https://openalex.org/W2898416733","https://openalex.org/W2911580050","https://openalex.org/W2941114335","https://openalex.org/W2947387656","https://openalex.org/W2951774549","https://openalex.org/W2953460162","https://openalex.org/W2974514154","https://openalex.org/W2991240192","https://openalex.org/W2995529796","https://openalex.org/W2998757713","https://openalex.org/W3003647318","https://openalex.org/W3101465817","https://openalex.org/W3106380050","https://openalex.org/W3216097587","https://openalex.org/W4206212643","https://openalex.org/W4221000689","https://openalex.org/W4249753629","https://openalex.org/W4285805545","https://openalex.org/W4299828299","https://openalex.org/W4301091646","https://openalex.org/W4303057417"],"related_works":["https://openalex.org/W3104422856","https://openalex.org/W4206864338","https://openalex.org/W4287867179","https://openalex.org/W3134690064","https://openalex.org/W4210726438","https://openalex.org/W4287752080","https://openalex.org/W3007674363","https://openalex.org/W3118984993","https://openalex.org/W2860329578","https://openalex.org/W3037706579"],"abstract_inverted_index":{"Multi-objective":[0],"Bayesian":[1],"optimization":[2,6,61,126,147],"is":[3],"a":[4,49,90,107],"sequential":[5],"strategy":[7],"in":[8,144],"which":[9],"an":[10,18,40,98],"optimizer":[11],"searches":[12],"for":[13,43,59,101,111],"optimal":[14],"solutions":[15],"by":[16,78],"maximizing":[17],"acquisition":[19,23,51],"function.":[20],"Most":[21],"existing":[22],"functions":[24],"assume":[25],"that":[26],"objectives":[27,38,77],"are":[28],"independent,":[29],"but":[30],"none":[31],"of":[32,56,70,104,118,142],"them":[33],"incorporates":[34],"the":[35,68,74,85,116,119,140],"correlations":[36,75],"among":[37],"through":[39],"explicit":[41,99],"formula":[42,100],"exact":[44,102],"computation.":[45],"This":[46,94],"paper":[47,95],"proposes":[48],"novel":[50],"function,":[52],"namely,":[53],"correlated":[54],"probability":[55,69],"improvement":[57,71],"(cPoI),":[58],"bi-objective":[60],"problems.":[62],"The":[63],"cPoI":[64,105,121,143],"method":[65,110],"builds":[66],"on":[67,128],"and":[72,106,132],"addresses":[73],"between":[76],"utilizing":[79],"3":[80],"distinct":[81],"approaches":[82],"to":[83],"compute":[84],"posterior":[86],"covariance":[87],"matrix":[88],"from":[89],"multi-task":[91],"Gaussian":[92],"process.":[93],"presents":[96],"both":[97],"computation":[103],"Monte":[108],"Carlo":[109],"approximating":[112],"it.":[113],"We":[114],"evaluate":[115],"performance":[117],"proposed":[120],"against":[122],"4":[123],"state-of-the-art":[124],"multi-objective":[125],"algorithms":[127],"8":[129],"artificial":[130],"benchmarks":[131],"1":[133],"real-world":[134],"problem.":[135],"Our":[136],"experimental":[137],"results":[138],"demonstrate":[139],"effectiveness":[141],"achieving":[145],"superior":[146],"performance.":[148]},"counts_by_year":[],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}