{"id":"https://openalex.org/W3159184652","doi":"https://doi.org/10.1109/ciss50987.2021.9400292","title":"No-Regret Algorithms for Time-Varying Bayesian Optimization","display_name":"No-Regret Algorithms for Time-Varying Bayesian Optimization","publication_year":2021,"publication_date":"2021-03-24","ids":{"openalex":"https://openalex.org/W3159184652","doi":"https://doi.org/10.1109/ciss50987.2021.9400292","mag":"3159184652"},"language":"en","primary_location":{"id":"doi:10.1109/ciss50987.2021.9400292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss50987.2021.9400292","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 55th Annual Conference on Information Sciences and Systems (CISS)","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/A5067378652","display_name":"Xingyu Zhou","orcid":"https://orcid.org/0000-0002-1771-8831"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingyu Zhou","raw_affiliation_strings":["Wayne State University, Detroit, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wayne State University, Detroit, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035752536","display_name":"Ness B. Shroff","orcid":"https://orcid.org/0000-0002-4606-6879"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ness Shroff","raw_affiliation_strings":["The Ohio State University, Columbus, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, USA","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3662,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.89430179,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":1.0,"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":0.9958000183105469,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9815000295639038,"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/regret","display_name":"Regret","score":0.8946689367294312},{"id":"https://openalex.org/keywords/reproducing-kernel-hilbert-space","display_name":"Reproducing kernel Hilbert space","score":0.7819676399230957},{"id":"https://openalex.org/keywords/frequentist-inference","display_name":"Frequentist inference","score":0.6819119453430176},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5756301879882812},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5460267066955566},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5441986918449402},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5373135805130005},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5163132548332214},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5073227286338806},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46975043416023254},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.4631113111972809},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4401853680610657},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.37763863801956177},{"id":"https://openalex.org/keywords/hilbert-space","display_name":"Hilbert space","score":0.33423006534576416},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.32201898097991943},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.26459044218063354},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20400097966194153},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.1404438614845276},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10943004488945007}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.8946689367294312},{"id":"https://openalex.org/C80884492","wikidata":"https://www.wikidata.org/wiki/Q3345678","display_name":"Reproducing kernel Hilbert space","level":3,"score":0.7819676399230957},{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.6819119453430176},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5756301879882812},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5460267066955566},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5441986918449402},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5373135805130005},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5163132548332214},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5073227286338806},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46975043416023254},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.4631113111972809},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4401853680610657},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.37763863801956177},{"id":"https://openalex.org/C62799726","wikidata":"https://www.wikidata.org/wiki/Q190056","display_name":"Hilbert space","level":2,"score":0.33423006534576416},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32201898097991943},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.26459044218063354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20400097966194153},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.1404438614845276},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10943004488945007},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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:10.1109/ciss50987.2021.9400292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss50987.2021.9400292","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 55th Annual Conference on Information Sciences and Systems (CISS)","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":28,"referenced_works":["https://openalex.org/W1502922572","https://openalex.org/W2009551863","https://openalex.org/W2119738618","https://openalex.org/W2271627589","https://openalex.org/W2491144192","https://openalex.org/W2880842812","https://openalex.org/W2927006103","https://openalex.org/W2951665052","https://openalex.org/W2951974212","https://openalex.org/W2958951938","https://openalex.org/W2962739885","https://openalex.org/W2962821829","https://openalex.org/W2963271096","https://openalex.org/W2970728282","https://openalex.org/W2970736459","https://openalex.org/W3019385773","https://openalex.org/W3037657204","https://openalex.org/W3092738648","https://openalex.org/W3121822496","https://openalex.org/W3124229194","https://openalex.org/W3173522316","https://openalex.org/W4288106770","https://openalex.org/W6629804754","https://openalex.org/W6694189648","https://openalex.org/W6755675075","https://openalex.org/W6765658323","https://openalex.org/W6767057814","https://openalex.org/W6780603889"],"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/W3118984993","https://openalex.org/W3037706579","https://openalex.org/W4401389295","https://openalex.org/W3157580548"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"consider":[4],"the":[5,33,40,44,49,52,57,75,81,104],"time-varying":[6,41,109],"Bayesian":[7],"optimization":[8],"problem.":[9],"The":[10],"unknown":[11],"function":[12,120],"at":[13],"each":[14,119],"time":[15],"is":[16,46,100,121],"assumed":[17],"to":[18,38,63],"lie":[19],"in":[20],"an":[21],"RKHS":[22,53],"(reproducing":[23],"kernel":[24,99],"Hilbert":[25],"space)":[26],"with":[27],"a":[28,97,114,122,125],"bounded":[29],"norm.":[30,54],"We":[31,55,73],"adopt":[32],"general":[34],"variation":[35,45],"budget":[36],"model":[37],"capture":[39],"environment,":[42],"and":[43,59,70],"characterized":[47],"by":[48],"change":[50],"of":[51,108],"adapt":[56],"restart":[58],"sliding":[60],"window":[61],"mechanism":[62],"introduce":[64],"two":[65],"GP-UCB":[66],"type":[67],"algorithms:":[68],"R-GP-UCB":[69],"SW-GP-UCB,":[71],"respectively.":[72],"derive":[74],"first":[76],"(frequentist)":[77],"regret":[78,83,106],"guarantee":[79],"on":[80],"dynamic":[82],"for":[84],"both":[85],"algorithms.":[86],"Our":[87],"results":[88,95],"not":[89],"only":[90],"recover":[91],"previous":[92,105],"linear":[93,98],"bandit":[94,112],"when":[96],"used,":[101],"but":[102],"complement":[103],"analysis":[107],"Gaussian":[110,126],"process":[111],"under":[113],"Bayesian-type":[115],"regularity":[116],"assumption,":[117],"i.e.,":[118],"sample":[123],"from":[124],"process.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
