{"id":"https://openalex.org/W2950103693","doi":"https://doi.org/10.1109/wsc.2016.7822140","title":"Warm starting Bayesian optimization","display_name":"Warm starting Bayesian optimization","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2950103693","doi":"https://doi.org/10.1109/wsc.2016.7822140","mag":"2950103693"},"language":"en","primary_location":{"id":"doi:10.1109/wsc.2016.7822140","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2016.7822140","pdf_url":null,"source":{"id":"https://openalex.org/S4363607936","display_name":"2016 Winter Simulation Conference (WSC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Winter Simulation Conference (WSC)","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/A5069492649","display_name":"Matthias Poloczek","orcid":"https://orcid.org/0000-0003-4178-5521"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthias Poloczek","raw_affiliation_strings":["School of Operations Research and Information Engineering, Cornell University, Ithaca, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Operations Research and Information Engineering, Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100628036","display_name":"Jialei Wang","orcid":"https://orcid.org/0000-0001-7556-4941"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jialei Wang","raw_affiliation_strings":["School of Operations Research and Information Engineering, Cornell University, Ithaca, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Operations Research and Information Engineering, Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039019367","display_name":"Peter I. Frazier","orcid":"https://orcid.org/0000-0002-3501-3341"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter I. Frazier","raw_affiliation_strings":["School of Operations Research and Information Engineering, Cornell University, Ithaca, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Operations Research and Information Engineering, Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"770","last_page":"781"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9997000098228455,"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":0.9997000098228455,"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/T11195","display_name":"Simulation Techniques and Applications","score":0.9980999827384949,"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"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9969000220298767,"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/bayesian-optimization","display_name":"Bayesian optimization","score":0.8164812922477722},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6903809309005737},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6502408385276794},{"id":"https://openalex.org/keywords/stochastic-optimization","display_name":"Stochastic optimization","score":0.6136996746063232},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5720115303993225},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5371518731117249},{"id":"https://openalex.org/keywords/metamodeling","display_name":"Metamodeling","score":0.48412761092185974},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4686911106109619},{"id":"https://openalex.org/keywords/continuous-optimization","display_name":"Continuous optimization","score":0.4629552960395813},{"id":"https://openalex.org/keywords/derivative-free-optimization","display_name":"Derivative-free optimization","score":0.4368331730365753},{"id":"https://openalex.org/keywords/metaheuristic","display_name":"Metaheuristic","score":0.419939249753952},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30311763286590576},{"id":"https://openalex.org/keywords/meta-optimization","display_name":"Meta-optimization","score":0.26537543535232544},{"id":"https://openalex.org/keywords/multi-swarm-optimization","display_name":"Multi-swarm optimization","score":0.24462515115737915},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20554745197296143},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20369252562522888}],"concepts":[{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.8164812922477722},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6903809309005737},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6502408385276794},{"id":"https://openalex.org/C194387892","wikidata":"https://www.wikidata.org/wiki/Q1747770","display_name":"Stochastic optimization","level":2,"score":0.6136996746063232},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5720115303993225},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5371518731117249},{"id":"https://openalex.org/C86610423","wikidata":"https://www.wikidata.org/wiki/Q1925081","display_name":"Metamodeling","level":2,"score":0.48412761092185974},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4686911106109619},{"id":"https://openalex.org/C92995354","wikidata":"https://www.wikidata.org/wiki/Q5165499","display_name":"Continuous optimization","level":4,"score":0.4629552960395813},{"id":"https://openalex.org/C29282572","wikidata":"https://www.wikidata.org/wiki/Q16977029","display_name":"Derivative-free optimization","level":4,"score":0.4368331730365753},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.419939249753952},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30311763286590576},{"id":"https://openalex.org/C4935549","wikidata":"https://www.wikidata.org/wiki/Q6822261","display_name":"Meta-optimization","level":3,"score":0.26537543535232544},{"id":"https://openalex.org/C122357587","wikidata":"https://www.wikidata.org/wiki/Q6934508","display_name":"Multi-swarm optimization","level":3,"score":0.24462515115737915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20554745197296143},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20369252562522888},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wsc.2016.7822140","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2016.7822140","pdf_url":null,"source":{"id":"https://openalex.org/S4363607936","display_name":"2016 Winter Simulation Conference (WSC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Winter Simulation Conference (WSC)","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":32,"referenced_works":["https://openalex.org/W1510052597","https://openalex.org/W1702387805","https://openalex.org/W1917966882","https://openalex.org/W1982568031","https://openalex.org/W2025207305","https://openalex.org/W2027826061","https://openalex.org/W2066561552","https://openalex.org/W2091010238","https://openalex.org/W2098718131","https://openalex.org/W2099201756","https://openalex.org/W2112372720","https://openalex.org/W2113145584","https://openalex.org/W2141771453","https://openalex.org/W2152074842","https://openalex.org/W2152435742","https://openalex.org/W2155927283","https://openalex.org/W2240302289","https://openalex.org/W2289490314","https://openalex.org/W2405673391","https://openalex.org/W2949644579","https://openalex.org/W3098139325","https://openalex.org/W3149369476","https://openalex.org/W4211049957","https://openalex.org/W4249925951","https://openalex.org/W6637338928","https://openalex.org/W6640127846","https://openalex.org/W6675200109","https://openalex.org/W6676544178","https://openalex.org/W6682467279","https://openalex.org/W6696058008","https://openalex.org/W6713927722","https://openalex.org/W7066967221"],"related_works":["https://openalex.org/W4287665271","https://openalex.org/W3126688642","https://openalex.org/W4386634475","https://openalex.org/W584331704","https://openalex.org/W2158873045","https://openalex.org/W308707143","https://openalex.org/W2353480216","https://openalex.org/W4256133869","https://openalex.org/W2596893084","https://openalex.org/W4220760338"],"abstract_inverted_index":{"We":[0],"develop":[1],"a":[2,23,36,109,123,137],"framework":[3],"for":[4,45],"warm-starting":[5],"Bayesian":[6,47,104],"optimization,":[7],"that":[8,19,39],"reduces":[9],"the":[10,33,90,93,113,128],"solution":[11,91],"time":[12,74],"required":[13],"to":[14,41,92,103,118,142,145],"solve":[15],"an":[16],"optimization":[17,48,56,66,88,105],"problem":[18],"is":[20,29],"one":[21,65],"in":[22],"sequence":[24],"of":[25,35,54,112,127,131,139],"related":[26,55,132],"problems.":[27],"This":[28],"useful":[30],"when":[31,59],"optimizing":[32],"output":[34],"stochastic":[37],"simulator":[38],"fails":[40],"provide":[42],"derivative":[43],"information,":[44],"which":[46,107],"methods":[49,81],"are":[50],"well-suited.":[51],"Solving":[52],"sequences":[53],"problems":[57],"arises":[58],"making":[60],"several":[61],"business":[62],"decisions":[63],"using":[64],"model":[67,126],"and":[68,135],"input":[69],"data":[70],"collected":[71],"over":[72],"different":[73],"periods":[75],"or":[76],"markets.":[77],"While":[78],"many":[79],"gradient-based":[80],"can":[82],"be":[83],"warm":[84,97],"started":[85],"by":[86],"initiating":[87],"at":[89],"previous":[94],"problem,":[95],"this":[96],"start":[98],"approach":[99,121],"does":[100],"not":[101],"apply":[102],"methods,":[106],"carry":[108],"full":[110],"metamodel":[111],"objective":[114,133],"function":[115],"from":[116],"iteration":[117],"iteration.":[119],"Our":[120],"builds":[122],"joint":[124],"statistical":[125],"entire":[129],"collection":[130],"functions,":[134],"uses":[136],"value":[138],"information":[140],"calculation":[141],"recommend":[143],"points":[144],"evaluate.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}
