{"id":"https://openalex.org/W4413680057","doi":"https://doi.org/10.23919/fusion65864.2025.11124043","title":"Bayesian Optimization for Robust Identification of Ornstein-Uhlenbeck Model","display_name":"Bayesian Optimization for Robust Identification of Ornstein-Uhlenbeck Model","publication_year":2025,"publication_date":"2025-07-07","ids":{"openalex":"https://openalex.org/W4413680057","doi":"https://doi.org/10.23919/fusion65864.2025.11124043"},"language":"en","primary_location":{"id":"doi:10.23919/fusion65864.2025.11124043","is_oa":false,"landing_page_url":"https://doi.org/10.23919/fusion65864.2025.11124043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 28th International Conference on Information Fusion (FUSION)","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/A5050722418","display_name":"Jun Xu","orcid":"https://orcid.org/0000-0001-7101-4280"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jinwen Xu","raw_affiliation_strings":["School of ECE, University of Georgia,Athens,GA,USA,30602"],"affiliations":[{"raw_affiliation_string":"School of ECE, University of Georgia,Athens,GA,USA,30602","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108932845","display_name":"Lu Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qin Lu","raw_affiliation_strings":["School of ECE, University of Georgia,Athens,GA,USA,30602"],"affiliations":[{"raw_affiliation_string":"School of ECE, University of Georgia,Athens,GA,USA,30602","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044127482","display_name":"Yaakov Bar\u2010Shalom","orcid":"https://orcid.org/0000-0003-1317-3368"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yaakov Bar-Shalom","raw_affiliation_strings":["University of Connecticut,Dept. of ECE,Storrs,CT,06269"],"affiliations":[{"raw_affiliation_string":"University of Connecticut,Dept. of ECE,Storrs,CT,06269","institution_ids":["https://openalex.org/I140172145"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050722418"],"corresponding_institution_ids":["https://openalex.org/I165733156"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33495851,"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":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.8471999764442444,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.8471999764442444,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.7781999707221985,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6096283197402954},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5885475873947144},{"id":"https://openalex.org/keywords/ornstein\u2013uhlenbeck-process","display_name":"Ornstein\u2013Uhlenbeck process","score":0.5845414400100708},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5429733395576477},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42302921414375305},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21813249588012695},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1812818944454193},{"id":"https://openalex.org/keywords/stochastic-process","display_name":"Stochastic process","score":0.17499902844429016}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6096283197402954},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5885475873947144},{"id":"https://openalex.org/C31634936","wikidata":"https://www.wikidata.org/wiki/Q1757587","display_name":"Ornstein\u2013Uhlenbeck process","level":3,"score":0.5845414400100708},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5429733395576477},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42302921414375305},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21813249588012695},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1812818944454193},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.17499902844429016},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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:10.23919/fusion65864.2025.11124043","is_oa":false,"landing_page_url":"https://doi.org/10.23919/fusion65864.2025.11124043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 28th International Conference on Information Fusion (FUSION)","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":17,"referenced_works":["https://openalex.org/W1531532259","https://openalex.org/W2024067571","https://openalex.org/W2053742104","https://openalex.org/W2089164997","https://openalex.org/W2096694793","https://openalex.org/W2103516605","https://openalex.org/W2117368100","https://openalex.org/W2166566250","https://openalex.org/W2179984775","https://openalex.org/W2192203593","https://openalex.org/W2216284590","https://openalex.org/W2328578724","https://openalex.org/W4211049957","https://openalex.org/W4317889697","https://openalex.org/W4362602242","https://openalex.org/W4390659094","https://openalex.org/W4403331795"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4297958632","https://openalex.org/W2007347740","https://openalex.org/W1485148789","https://openalex.org/W4290098506","https://openalex.org/W2006484586","https://openalex.org/W2788316749","https://openalex.org/W2949809604"],"abstract_inverted_index":{"This":[0,213],"paper":[1],"deals":[2],"with":[3,62],"the":[4,7,23,27,33,36,40,47,55,79,94,105,112,118,141,146,166,171,179,184,189,195,202,221,225,233,237],"identification":[5,177],"of":[6,26,35,39,111,157,170,178],"stochastic":[8,180],"Ornstein-Uhlenbeck":[9],"(OU)":[10],"process":[11,28,89],"error":[12,160],"model,":[13],"which":[14,84,207],"is":[15,114,151],"characterized":[16],"by":[17,140,188,220,230],"an":[18],"inverse":[19,203],"time":[20,204],"constant,":[21,205],"and":[22,29,58,101,129,145,162,168],"unknown":[24],"variances":[25],"observation":[30],"noises.":[31],"Although":[32],"availability":[34],"explicit":[37],"expression":[38],"log-likelihood":[41],"function":[42,96],"allows":[43],"one":[44],"to":[45,103],"obtain":[46],"maximum":[48],"likelihood":[49],"estimator":[50,135,191],"(MLE),":[51],"this":[52],"entails":[53],"evaluating":[54],"nontrivial":[56],"gradient":[57],"also":[59],"often":[60],"struggles":[61],"local":[63],"optima.":[64],"To":[65],"address":[66],"these":[67],"limitations,":[68],"we":[69],"put":[70],"forth":[71],"a":[72,87,152,210],"sample-efficient":[73],"global":[74],"optimization":[75,81],"approach":[76],"based":[77],"on":[78,86,125],"Bayesian":[80],"(BO)":[82],"framework,":[83],"relies":[85],"Gaussian":[88],"(GP)":[90],"surrogate":[91],"model":[92],"for":[93,176,201,224],"objective":[95,113,238],"that":[97,133],"effectively":[98],"balances":[99],"exploration":[100],"exploitation":[102],"select":[104],"query":[106],"points.":[107],"Specifically,":[108],"each":[109],"evaluation":[110],"implemented":[115,139],"efficiently":[116],"through":[117,232],"Kalman":[119],"filter":[120],"(KF)":[121],"recursion.":[122],"Comprehensive":[123],"experiments":[124],"various":[126],"parameter":[127],"scenarios":[128],"sampling":[130],"intervals":[131],"corroborate":[132],"BO-based":[134,190],"consistently":[136],"outperforms":[137],"MLE":[138],"steady-state":[142],"KF":[143],"approximation":[144],"expectation-maximization":[147],"algorithm":[148],"(whose":[149],"derivation":[150],"side":[153],"contribution)":[154],"in":[155],"terms":[156],"root":[158],"meansquare":[159],"(RMSE)":[161],"statistical":[163],"consistency,":[164],"confirming":[165],"effectiveness":[167],"robustness":[169],"<tex":[172],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[173],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{B":[174],"O}$</tex>":[175],"OU":[181],"process.":[182],"Notably,":[183],"RMSE":[185],"values":[186],"produced":[187],"are":[192],"smaller":[193],"than":[194],"classical":[196],"Cram\u00e9rRao":[197],"lower":[198],"bound,":[199],"especially":[200],"estimating":[206],"has":[208],"been":[209],"long-standing":[211],"challenge.":[212],"seemingly":[214],"counterintuitive":[215],"result":[216],"can":[217],"be":[218],"explained":[219],"data-driven":[222],"prior":[223,235],"learning":[226],"parameters":[227],"indirectly":[228],"injected":[229],"BO":[231],"GP":[234],"over":[236],"function.":[239]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}