{"id":"https://openalex.org/W2963668165","doi":"https://doi.org/10.1109/camsap.2017.8313092","title":"Sequential detection of low-rank changes using extreme eigenvalues","display_name":"Sequential detection of low-rank changes using extreme eigenvalues","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2963668165","doi":"https://doi.org/10.1109/camsap.2017.8313092","mag":"2963668165"},"language":"en","primary_location":{"id":"doi:10.1109/camsap.2017.8313092","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap.2017.8313092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","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/A5075007159","display_name":"Liyan Xie","orcid":"https://orcid.org/0000-0003-3009-4514"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Liyan Xie","raw_affiliation_strings":["H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047736740","display_name":"Yao Xie","orcid":"https://orcid.org/0000-0001-6777-2951"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yao Xie","raw_affiliation_strings":["H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075007159"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24020412,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"114","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9767000079154968,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9560999870300293,"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/covariance-matrix","display_name":"Covariance matrix","score":0.7634761929512024},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.6449690461158752},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5837975740432739},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.577392041683197},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.5750546455383301},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5418970584869385},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.521658182144165},{"id":"https://openalex.org/keywords/identity-matrix","display_name":"Identity matrix","score":0.5207357406616211},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5052240490913391},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5018811225891113},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5009098052978516},{"id":"https://openalex.org/keywords/extreme-point","display_name":"Extreme point","score":0.4867837131023407},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.44963735342025757},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4288960099220276},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.42592698335647583},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4142315685749054},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3712940216064453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2875669598579407},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.2040632665157318},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.13357067108154297},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07523444294929504}],"concepts":[{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.7634761929512024},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.6449690461158752},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5837975740432739},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.577392041683197},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.5750546455383301},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5418970584869385},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.521658182144165},{"id":"https://openalex.org/C134567657","wikidata":"https://www.wikidata.org/wiki/Q193794","display_name":"Identity matrix","level":3,"score":0.5207357406616211},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5052240490913391},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5018811225891113},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5009098052978516},{"id":"https://openalex.org/C39847760","wikidata":"https://www.wikidata.org/wiki/Q1385465","display_name":"Extreme point","level":2,"score":0.4867837131023407},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.44963735342025757},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4288960099220276},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.42592698335647583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4142315685749054},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3712940216064453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2875669598579407},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.2040632665157318},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.13357067108154297},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07523444294929504},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/camsap.2017.8313092","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap.2017.8313092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","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":16,"referenced_works":["https://openalex.org/W1520752838","https://openalex.org/W1875173799","https://openalex.org/W2002912011","https://openalex.org/W2006452405","https://openalex.org/W2058018849","https://openalex.org/W2060581589","https://openalex.org/W2083694956","https://openalex.org/W2091082553","https://openalex.org/W2106084579","https://openalex.org/W2142110788","https://openalex.org/W2237587256","https://openalex.org/W2410650029","https://openalex.org/W2962974474","https://openalex.org/W2963105348","https://openalex.org/W3098548805","https://openalex.org/W3102480238"],"related_works":["https://openalex.org/W3189643850","https://openalex.org/W2375407244","https://openalex.org/W1983393909","https://openalex.org/W3210391122","https://openalex.org/W2040150569","https://openalex.org/W1912896918","https://openalex.org/W2468095590","https://openalex.org/W2132174924","https://openalex.org/W1911540634","https://openalex.org/W2013909972"],"abstract_inverted_index":{"We":[0],"study":[1],"the":[2,10,16,40,43,47,61,70,73,89,96,104],"problem":[3],"of":[4,46,69,91,107,114],"detecting":[5,111],"an":[6,25,56],"abrupt":[7],"change":[8,113],"to":[9,24,60,95],"signal":[11],"covariance":[12,17,49],"matrix.":[13,30,50],"In":[14],"particular,":[15],"changes":[18],"from":[19,77],"a":[20,84,115],"\u201cwhite\u201d":[21],"identity":[22],"matrix":[23,79],"unknown":[26],"spiked":[27],"or":[28],"low-rank":[29],"Two":[31],"sequential":[32],"change-point":[33],"detection":[34,66],"procedures":[35],"are":[36],"presented,":[37],"based":[38],"on":[39],"largest":[41],"and":[42,64,81],"smallest":[44],"eigenvalues":[45],"sample":[48],"To":[51],"control":[52],"false-alarm-rate,":[53],"we":[54],"present":[55],"accurate":[57],"theoretical":[58],"approximation":[59],"average-run-length":[62],"(ARL)":[63],"expected":[65],"delay":[67],"(EDD)":[68],"detection,":[71],"leveraging":[72],"extreme":[74],"eigenvalue":[75],"distributions":[76],"random":[78],"theory":[80],"by":[82],"capturing":[83],"non-negligible":[85],"temporal":[86],"correlation":[87],"in":[88],"sequence":[90],"scan":[92],"statistics":[93],"due":[94],"sliding":[97],"window":[98],"approach.":[99],"Real":[100],"data":[101],"examples":[102],"demonstrate":[103],"good":[105],"performance":[106],"our":[108],"method":[109],"for":[110],"behavior":[112],"swarm.":[116]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}