{"id":"https://openalex.org/W4297017196","doi":"https://doi.org/10.1080/00401706.2022.2127914","title":"A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling","display_name":"A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4297017196","doi":"https://doi.org/10.1080/00401706.2022.2127914"},"language":"en","primary_location":{"id":"doi:10.1080/00401706.2022.2127914","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2022.2127914","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-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/A5047695385","display_name":"Jie Guo","orcid":"https://orcid.org/0000-0002-8319-524X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Guo","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8319-524X","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100652901","display_name":"Hao Yan","orcid":"https://orcid.org/0000-0002-4322-7323"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Yan","raw_affiliation_strings":["Arizona State University, Tempe, AZ"],"raw_orcid":"https://orcid.org/0000-0002-4322-7323","affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100374122","display_name":"Chen Zhang","orcid":"https://orcid.org/0000-0002-4767-9597"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Zhang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4767-9597","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100374122"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.9782,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.92136572,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"65","issue":"2","first_page":"179","last_page":"191"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9926000237464905,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.6183702349662781},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5852766036987305},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5719764828681946},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4752366840839386},{"id":"https://openalex.org/keywords/bayes-factor","display_name":"Bayes factor","score":0.46732819080352783},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42678582668304443},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.42511945962905884},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.4211609661579132},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.41934049129486084},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.403607040643692},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38158318400382996},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3602973520755768},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32212623953819275},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21534055471420288},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.12976780533790588}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6183702349662781},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5852766036987305},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5719764828681946},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4752366840839386},{"id":"https://openalex.org/C142291917","wikidata":"https://www.wikidata.org/wiki/Q4165283","display_name":"Bayes factor","level":4,"score":0.46732819080352783},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42678582668304443},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.42511945962905884},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.4211609661579132},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.41934049129486084},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.403607040643692},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38158318400382996},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3602973520755768},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32212623953819275},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21534055471420288},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.12976780533790588},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/00401706.2022.2127914","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2022.2127914","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2445352823","display_name":"\u57fa\u4e8e\u590d\u6742\u8f6e\u5ed3\u6570\u636e\u7684\u7edf\u8ba1\u5efa\u6a21\u548c\u5728\u7ebf\u76d1\u63a7\u7814\u7a76","funder_award_id":"71901131","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7236899727","display_name":"\u5de5\u4e1a\u5927\u6570\u636e\u73af\u5883\u4e0b\u9762\u5411\u667a\u80fd\u5236\u9020\u7cfb\u7edf\u7684\u8d28\u91cf\u79d1\u5b66\u7ba1\u63a7\u65b9\u6cd5\u7814\u7a76","funder_award_id":"71932006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7787109876","display_name":null,"funder_award_id":"9222014","funder_id":"https://openalex.org/F4320321843","funder_display_name":"Bulgarian National Science Fund"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321843","display_name":"Bulgarian National Science Fund","ror":"https://ror.org/05eg49r29"},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W35251828","https://openalex.org/W1479584399","https://openalex.org/W1483883706","https://openalex.org/W1588948804","https://openalex.org/W1911551976","https://openalex.org/W1969415786","https://openalex.org/W1971084072","https://openalex.org/W1993631132","https://openalex.org/W2004249081","https://openalex.org/W2007069447","https://openalex.org/W2027973545","https://openalex.org/W2030854293","https://openalex.org/W2032230252","https://openalex.org/W2045067839","https://openalex.org/W2055025635","https://openalex.org/W2056980115","https://openalex.org/W2068913238","https://openalex.org/W2093994886","https://openalex.org/W2123649031","https://openalex.org/W2147426468","https://openalex.org/W2150871663","https://openalex.org/W2158142902","https://openalex.org/W2342910067","https://openalex.org/W2506282021","https://openalex.org/W2607420770","https://openalex.org/W2612481336","https://openalex.org/W2612690371","https://openalex.org/W2734129016","https://openalex.org/W2788365376","https://openalex.org/W2790665460","https://openalex.org/W2898699838","https://openalex.org/W2903909161","https://openalex.org/W2944412641","https://openalex.org/W2964132277","https://openalex.org/W2990138404","https://openalex.org/W2990611428","https://openalex.org/W3022723022","https://openalex.org/W3044267241","https://openalex.org/W3080262031","https://openalex.org/W3084695296","https://openalex.org/W3089200789","https://openalex.org/W3098452830","https://openalex.org/W3099090856","https://openalex.org/W3101584830","https://openalex.org/W3101816981","https://openalex.org/W3105261654","https://openalex.org/W3137278554","https://openalex.org/W4200399832","https://openalex.org/W4292156489","https://openalex.org/W6678757208","https://openalex.org/W6780241773"],"related_works":["https://openalex.org/W2030346622","https://openalex.org/W2080772702","https://openalex.org/W2286136095","https://openalex.org/W322979909","https://openalex.org/W3126772094","https://openalex.org/W2000843381","https://openalex.org/W2887093192","https://openalex.org/W3034669169","https://openalex.org/W4287870652","https://openalex.org/W3004547119"],"abstract_inverted_index":{"This":[0],"article":[1],"proposes":[2],"a":[3,17,41,83,142,176],"Bayesian":[4,85,111],"learning":[5],"framework":[6],"for":[7,148],"online":[8],"change":[9,42],"detection":[10,43,72,124,131],"of":[11,19,137,157,165],"high-dimensional":[12,95],"data":[13],"streams":[14],"where":[15,102],"only":[16],"subset":[18],"variables":[20,66,153],"can":[21],"be":[22,55],"observed":[23],"at":[24],"each":[25],"time":[26],"point":[27],"due":[28],"to":[29,39,57,67,69,92],"limited":[30],"sensing":[31,65],"capacities.":[32],"On":[33,49],"the":[34,50,52,62,71,94,103,116,123,130,134,150,155],"one":[35],"hand,":[36],"we":[37],"need":[38],"build":[40],"scheme":[44,53],"based":[45],"on":[46],"partial":[47],"observations.":[48],"other,":[51],"should":[54],"able":[56],"adaptively":[58],"and":[59,99,159,163,175],"actively":[60],"select":[61],"most":[63],"critical":[64],"observe":[68],"maximize":[70],"power.":[73],"To":[74],"address":[75],"these":[76],"two":[77],"points,":[78],"in":[79,170],"this":[80],"article,":[81],"first,":[82],"novel":[84],"Spike-Slab":[86],"Composite":[87],"Decomposition":[88],"(BSSCD)":[89],"is":[90,120,146],"proposed":[91,147],"decompose":[93],"signals":[96],"onto":[97],"normal":[98],"abnormal":[100],"bases,":[101],"projection":[104],"coefficients":[105],"are":[106,168],"efficiently":[107],"estimated":[108],"via":[109],"variational":[110],"inference.":[112],"Built":[113],"upon":[114],"it,":[115],"posterior":[117],"Bayes":[118],"factor":[119],"constructed":[121],"as":[122,133],"statistic.":[125],"Second,":[126],"by":[127],"further":[128],"formulating":[129],"statistic":[132],"reward":[135],"function":[136],"combinatorial":[138],"multi-armed":[139],"bandit":[140],"(CMAB),":[141],"Thompson":[143],"sampling":[144],"strategy":[145],"selecting":[149],"potential":[151],"changed":[152],"with":[154,172],"balance":[156],"exploration":[158],"exploitation.":[160],"The":[161],"efficacy":[162],"applicability":[164],"our":[166],"method":[167],"demonstrated":[169],"practice":[171],"numerical":[173],"studies":[174],"real":[177],"case":[178],"study.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":7}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}