{"id":"https://openalex.org/W4384698630","doi":"https://doi.org/10.1007/s10472-023-09883-w","title":"Bayesian optimization over the probability simplex","display_name":"Bayesian optimization over the probability simplex","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4384698630","doi":"https://doi.org/10.1007/s10472-023-09883-w"},"language":"en","primary_location":{"id":"doi:10.1007/s10472-023-09883-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10472-023-09883-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10472-023-09883-w.pdf","source":{"id":"https://openalex.org/S90199469","display_name":"Annals of Mathematics and Artificial Intelligence","issn_l":"1012-2443","issn":["1012-2443","1573-7470"],"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":"Annals of Mathematics and Artificial Intelligence","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/s10472-023-09883-w.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007832994","display_name":"Antonio Candelieri","orcid":"https://orcid.org/0000-0003-1431-576X"},"institutions":[{"id":"https://openalex.org/I66752286","display_name":"University of Milano-Bicocca","ror":"https://ror.org/01ynf4891","country_code":"IT","type":"education","lineage":["https://openalex.org/I66752286"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Antonio Candelieri","raw_affiliation_strings":["Department of Economics, Management, and Statistics, University of Milano-Bicocca, Milan, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Economics, Management, and Statistics, University of Milano-Bicocca, Milan, Italy","institution_ids":["https://openalex.org/I66752286"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052850594","display_name":"Andrea Ponti","orcid":"https://orcid.org/0000-0003-4187-4209"},"institutions":[{"id":"https://openalex.org/I66752286","display_name":"University of Milano-Bicocca","ror":"https://ror.org/01ynf4891","country_code":"IT","type":"education","lineage":["https://openalex.org/I66752286"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Andrea Ponti","raw_affiliation_strings":["Department of Economics, Management, and Statistics, University of Milano-Bicocca, Milan, Italy"],"raw_orcid":"https://orcid.org/0000-0003-4187-4209","affiliations":[{"raw_affiliation_string":"Department of Economics, Management, and Statistics, University of Milano-Bicocca, Milan, Italy","institution_ids":["https://openalex.org/I66752286"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011390491","display_name":"Francesco Archetti","orcid":"https://orcid.org/0000-0003-1131-3830"},"institutions":[{"id":"https://openalex.org/I66752286","display_name":"University of Milano-Bicocca","ror":"https://ror.org/01ynf4891","country_code":"IT","type":"education","lineage":["https://openalex.org/I66752286"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Archetti","raw_affiliation_strings":["Department of Computer Science, University of Milano-Bicocca, Systems, and Communication, Milan, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Milano-Bicocca, Systems, and Communication, Milan, Italy","institution_ids":["https://openalex.org/I66752286"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5052850594"],"corresponding_institution_ids":["https://openalex.org/I66752286"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14519363,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"93","issue":"1","first_page":"77","last_page":"91"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.993399977684021,"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":0.993399977684021,"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":0.9911999702453613,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9739999771118164,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6179945468902588},{"id":"https://openalex.org/keywords/simplex","display_name":"Simplex","score":0.6168789863586426},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5551797151565552},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.5265560150146484},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.4794786870479584},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4527660608291626},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.41850847005844116},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41460996866226196},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38398346304893494},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09637859463691711},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09033703804016113}],"concepts":[{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6179945468902588},{"id":"https://openalex.org/C62438384","wikidata":"https://www.wikidata.org/wiki/Q331350","display_name":"Simplex","level":2,"score":0.6168789863586426},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5551797151565552},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.5265560150146484},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.4794786870479584},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4527660608291626},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.41850847005844116},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41460996866226196},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38398346304893494},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09637859463691711},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09033703804016113}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10472-023-09883-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10472-023-09883-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10472-023-09883-w.pdf","source":{"id":"https://openalex.org/S90199469","display_name":"Annals of Mathematics and Artificial Intelligence","issn_l":"1012-2443","issn":["1012-2443","1573-7470"],"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":"Annals of Mathematics and Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:boa.unimib.it:10281/578561","is_oa":true,"landing_page_url":"https://hdl.handle.net/10281/578561","pdf_url":null,"source":{"id":"https://openalex.org/S4306401259","display_name":"BOA (University of Milano-Bicocca)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66752286","host_organization_name":"University of Milano-Bicocca","host_organization_lineage":["https://openalex.org/I66752286"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s10472-023-09883-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10472-023-09883-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10472-023-09883-w.pdf","source":{"id":"https://openalex.org/S90199469","display_name":"Annals of Mathematics and Artificial Intelligence","issn_l":"1012-2443","issn":["1012-2443","1573-7470"],"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":"Annals of Mathematics and Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384698630.pdf"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W107774600","https://openalex.org/W1944513002","https://openalex.org/W1984235709","https://openalex.org/W2038497950","https://openalex.org/W2061144551","https://openalex.org/W2089035496","https://openalex.org/W2122321062","https://openalex.org/W2124959221","https://openalex.org/W2519388618","https://openalex.org/W2792164701","https://openalex.org/W2907344895","https://openalex.org/W2960816872","https://openalex.org/W2976818350","https://openalex.org/W3010758268","https://openalex.org/W3035145762","https://openalex.org/W3045324548","https://openalex.org/W3091152815","https://openalex.org/W3095730670","https://openalex.org/W3099171794","https://openalex.org/W3105956282","https://openalex.org/W3212574796","https://openalex.org/W4206471589","https://openalex.org/W4213458919","https://openalex.org/W4238746485","https://openalex.org/W4311156955","https://openalex.org/W4319239109","https://openalex.org/W6636804120"],"related_works":["https://openalex.org/W2063021680","https://openalex.org/W3106461837","https://openalex.org/W4364381099","https://openalex.org/W3168182983","https://openalex.org/W4321472004","https://openalex.org/W2357922472","https://openalex.org/W2384278689","https://openalex.org/W4382203014","https://openalex.org/W2783383155","https://openalex.org/W4379928930"],"abstract_inverted_index":{"Abstract":[0],"Gaussian":[1],"Process":[2],"based":[3,97,104],"Bayesian":[4,139,154],"Optimization":[5],"is":[6,57,78],"largely":[7],"adopted":[8],"for":[9],"solving":[10],"problems":[11,125],"where":[12],"the":[13,24,34,40,65,72,75,85,102,109,138,143,158],"inputs":[14,25],"are":[15,31,94],"in":[16,39,142],"Euclidean":[17],"spaces.":[18],"In":[19],"this":[20,90],"paper":[21],"we":[22,44,113],"associate":[23],"to":[26,60,80,131],"discrete":[27],"probability":[28,35,86,144],"distributions":[29],"which":[30],"elements":[32],"of":[33,118,124,160],"simplex.":[36,87],"To":[37,88],"search":[38],"new":[41],"design":[42],"space,":[43],"need":[45],"a":[46,115,122],"distance":[47,53],"between":[48],"distributions.":[49],"The":[50],"optimal":[51],"transport":[52],"(aka":[54],"Wasserstein":[55],"distance)":[56],"chosen":[58],"due":[59],"its":[61],"mathematical":[62],"structure":[63],"and":[64,74,101,108],"computational":[66,119],"strategies":[67],"enabled":[68],"by":[69],"it.":[70],"Both":[71],"GP":[73],"acquisition":[76,82],"function":[77],"generalized":[79],"an":[81,147],"functional":[83,91],"over":[84,152],"optimize":[89],"two":[92],"methods":[93],"proposed,":[95],"one":[96],"on":[98,105,121],"auto":[99],"differentiation":[100],"other":[103],"proximal-point":[106],"algorithm":[107,149],"gradient":[110],"flow.":[111],"Finally,":[112],"report":[114],"preliminary":[116],"set":[117],"results":[120,134],"class":[123],"whose":[126,150],"dimension":[127],"ranges":[128],"from":[129],"5":[130],"100.":[132],"These":[133],"show":[135],"that":[136],"embedding":[137],"optimization":[140,155],"process":[141],"simplex":[145],"enables":[146],"effective":[148],"performance":[151],"standard":[153],"improves":[156],"with":[157],"increase":[159],"problem":[161],"dimensionality.":[162]},"counts_by_year":[],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
