{"id":"https://openalex.org/W4405909368","doi":"https://doi.org/10.1109/itw61385.2024.10807011","title":"Large Deviations for Outlier Hypothesis Testing with Distribution Uncertainty","display_name":"Large Deviations for Outlier Hypothesis Testing with Distribution Uncertainty","publication_year":2024,"publication_date":"2024-11-24","ids":{"openalex":"https://openalex.org/W4405909368","doi":"https://doi.org/10.1109/itw61385.2024.10807011"},"language":"en","primary_location":{"id":"doi:10.1109/itw61385.2024.10807011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw61385.2024.10807011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Information Theory Workshop (ITW)","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/A5013386113","display_name":"Xiaotian Zhang","orcid":"https://orcid.org/0000-0001-7864-4218"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaotian Zhang","raw_affiliation_strings":["School of Cyber Science and Technology (CST), Beihang University,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Technology (CST), Beihang University,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071389455","display_name":"Jun Diao","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Diao","raw_affiliation_strings":["School of Cyber Science and Technology (CST), Beihang University,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Technology (CST), Beihang University,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048143843","display_name":"Lin Zhou","orcid":"https://orcid.org/0000-0003-4810-6704"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Zhou","raw_affiliation_strings":["School of Cyber Science and Technology (CST), Beihang University,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Technology (CST), Beihang University,China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"61","last_page":"66"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.989799976348877,"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":0.989799976348877,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.984499990940094,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.968500018119812,"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/outlier","display_name":"Outlier","score":0.6400920152664185},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5801720023155212},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.42140090465545654},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.417715847492218},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.38980624079704285},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3514491021633148},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33212020993232727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30200961232185364},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2124902904033661}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6400920152664185},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5801720023155212},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.42140090465545654},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.417715847492218},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.38980624079704285},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3514491021633148},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33212020993232727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30200961232185364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2124902904033661}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itw61385.2024.10807011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw61385.2024.10807011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Information Theory Workshop (ITW)","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":22,"referenced_works":["https://openalex.org/W2006433789","https://openalex.org/W2014002306","https://openalex.org/W2033387638","https://openalex.org/W2112142266","https://openalex.org/W2346099651","https://openalex.org/W2397674684","https://openalex.org/W2759246051","https://openalex.org/W2915876425","https://openalex.org/W2963090585","https://openalex.org/W2963252366","https://openalex.org/W3080501010","https://openalex.org/W3181906970","https://openalex.org/W3217507509","https://openalex.org/W4213248213","https://openalex.org/W4221138869","https://openalex.org/W4226134326","https://openalex.org/W4246098931","https://openalex.org/W4250589301","https://openalex.org/W4295789122","https://openalex.org/W4366310824","https://openalex.org/W6752005543","https://openalex.org/W6767692553"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2510582230","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729"],"abstract_inverted_index":{"The":[0],"task":[1],"of":[2,13,42,119,138,145,157],"outlier":[3,56,79],"hypothesis":[4,57],"testing":[5,58],"is":[6,66,80,94,154],"to":[7,72,86],"identify":[8],"outliers":[9,32],"from":[10,24,35,68,82],"a":[11,69,73,83,87,112,155],"set":[12],"observed":[14],"sequences,":[15],"where":[16,91],"most":[17],"sequences":[18,30],"named":[19],"nominal":[20,25,64,75,99,163],"samples":[21],"are":[22,33,103],"generated":[23,34,67,81],"distributions":[26,102],"and":[27,50,77,100,115,126,148,164],"the":[28,40,92,107,117,124,131,136,142,151,158],"rest":[29],"called":[31],"anomalous":[36,89,101,165],"distributions.":[37,166],"Inspired":[38],"by":[39,48],"study":[41,55],"binary":[43],"classification":[44],"with":[45,59],"distribution":[46,60,70,76,84,139],"mismatch":[47],"Hsu":[49],"Wang":[51],"(ISIT":[52],"2020),":[53],"we":[54,110,134],"uncertainty.":[61],"Specifically,":[62],"each":[63,78],"sequence":[65],"close":[71,85],"centered":[74,88,162],"distribution,":[90],"closeness":[93],"measured":[95],"via":[96],"L-norms.":[97],"Both":[98],"unknown.":[104],"To":[105],"solve":[106],"above":[108],"problem,":[109],"propose":[111],"threshold-based":[113],"test":[114,121],"characterize":[116],"performance":[118,144],"our":[120,146],"in":[122,130],"both":[123],"Chernoff's":[125],"Stein's":[127,132],"regimes.":[128],"Furthermore,":[129],"regime,":[133],"analyze":[135],"impact":[137],"uncertainty":[140],"on":[141],"asymptotic":[143],"result":[147],"show":[149],"that":[150],"dominant":[152],"term":[153],"function":[156],"likelihood":[159],"ratio":[160],"between":[161]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}