{"id":"https://openalex.org/W4402673665","doi":"https://doi.org/10.1109/e-science62913.2024.10678675","title":"Enhancing Bayesian Optimization with NLML-Based Transfer Learning","display_name":"Enhancing Bayesian Optimization with NLML-Based Transfer Learning","publication_year":2024,"publication_date":"2024-09-16","ids":{"openalex":"https://openalex.org/W4402673665","doi":"https://doi.org/10.1109/e-science62913.2024.10678675"},"language":"en","primary_location":{"id":"doi:10.1109/e-science62913.2024.10678675","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/e-science62913.2024.10678675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on e-Science (e-Science)","raw_type":"proceedings-article"},"type":"article","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/A5081993894","display_name":"Yanchen Li","orcid":"https://orcid.org/0009-0007-9752-7755"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"Osaka University","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yanchen Li","raw_affiliation_strings":["Osaka University,Graduate School of Information Science and Technology,Osaka,Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University,Graduate School of Information Science and Technology,Osaka,Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032985510","display_name":"Taku Tsuzuki","orcid":null},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"Osaka University","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]},{"id":"https://openalex.org/I3133035077","display_name":"Ube Frontier University","ror":"https://ror.org/03sgcr744","country_code":"JP","type":"education","lineage":["https://openalex.org/I3133035077"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taku Tsuzuki","raw_affiliation_strings":["Osaka University,Graduate School of Frontier Biosciences,Osaka,Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University,Graduate School of Frontier Biosciences,Osaka,Japan","institution_ids":["https://openalex.org/I3133035077","https://openalex.org/I98285908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081993894"],"corresponding_institution_ids":["https://openalex.org/I98285908"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13865233,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.8942000269889832,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.8942000269889832,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.8269000053405762,"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/T10028","display_name":"Topic Modeling","score":0.774399995803833,"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":0.6639277338981628},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6355268955230713},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5540112257003784},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4923471212387085},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4193163216114044},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3310897648334503}],"concepts":[{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.6639277338981628},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6355268955230713},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5540112257003784},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4923471212387085},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4193163216114044},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3310897648334503}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/e-science62913.2024.10678675","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/e-science62913.2024.10678675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on e-Science (e-Science)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W61667912","https://openalex.org/W2030006024","https://openalex.org/W2192203593","https://openalex.org/W2964125718","https://openalex.org/W4291125279","https://openalex.org/W6769040946","https://openalex.org/W6794927494"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Bayesian":[0],"optimization":[1,13],"(BO)":[2],"is":[3,50],"a":[4,71,80],"powerful":[5],"machine":[6],"learning":[7,30,49,82],"method":[8,46,83],"used":[9],"to":[10,51,101],"solve":[11],"black-box":[12],"problems,":[14],"such":[15],"as":[16],"exploring":[17],"optimal":[18],"conditions":[19],"for":[20,66],"cell":[21],"culturing.":[22],"For":[23],"problems":[24],"with":[25],"high":[26],"evaluation":[27],"costs,":[28],"transfer":[29,81],"from":[31],"similar":[32],"source":[33],"tasks":[34,58],"helps":[35,121],"BO":[36,122],"find":[37],"solutions":[38,125],"more":[39],"quickly,":[40],"thereby":[41,109],"reducing":[42],"costs.":[43],"A":[44],"popular":[45],"of":[47,56,105],"transferring":[48],"merge":[52],"the":[53,64,86,97,103,106],"surrogate":[54,99,113],"models":[55],"previous":[57],"through":[59],"linear":[60,68],"combination.":[61],"To":[62],"calculate":[63],"weights":[65,87],"this":[67],"combination":[69,78],"in":[70],"fine-grained":[72],"manner,":[73],"we":[74],"propose":[75],"adaptive":[76],"distributions":[77],"(ADC),":[79],"that":[84,119],"optimizes":[85,96],"using":[88],"negative":[89],"log":[90],"marginal":[91],"likelihood":[92],"(NLML).":[93],"NLML":[94],"directly":[95],"merged":[98],"model":[100],"fit":[102],"distribution":[104],"target":[107],"function,":[108],"building":[110],"an":[111],"accurate":[112],"model.":[114],"Our":[115],"experimental":[116],"results":[117],"indicate":[118],"ADC":[120],"explore":[123],"better":[124],"than":[126],"ranking-based":[127],"methods.":[128]},"counts_by_year":[],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}