{"id":"https://openalex.org/W3174350961","doi":"https://doi.org/10.1109/tsp.2022.3162120","title":"A Fast and Efficient Change-Point Detection Framework Based on Approximate $k$-Nearest Neighbor Graphs","display_name":"A Fast and Efficient Change-Point Detection Framework Based on Approximate $k$-Nearest Neighbor Graphs","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W3174350961","doi":"https://doi.org/10.1109/tsp.2022.3162120","mag":"3174350961"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2022.3162120","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3162120","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","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/A5100348090","display_name":"Yiwei Liu","orcid":"https://orcid.org/0000-0003-1998-4807"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yi-Wei Liu","raw_affiliation_strings":["Department of Statistics, University of California, Davis, Davis, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of California, Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100353555","display_name":"Hao Chen","orcid":"https://orcid.org/0000-0002-4597-2773"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Chen","raw_affiliation_strings":["Department of Statistics, University of California, Davis, Davis, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of California, Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100348090"],"corresponding_institution_ids":["https://openalex.org/I84218800"],"apc_list":null,"apc_paid":null,"fwci":2.4315,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.89202836,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"70","issue":null,"first_page":"1976","last_page":"1986"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9550999999046326,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9550999999046326,"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":0.9312999844551086,"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/T12303","display_name":"Tensor decomposition and applications","score":0.929099977016449,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"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/notation","display_name":"Notation","score":0.641423225402832},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4471295177936554},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.433212548494339},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.419479101896286},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4193260669708252},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.3840675950050354},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.3736802935600281},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.12684038281440735}],"concepts":[{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.641423225402832},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4471295177936554},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.433212548494339},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.419479101896286},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4193260669708252},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.3840675950050354},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.3736802935600281},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.12684038281440735},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2022.3162120","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3162120","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W93600389","https://openalex.org/W639907764","https://openalex.org/W1577286032","https://openalex.org/W2038102631","https://openalex.org/W2044535354","https://openalex.org/W2047287351","https://openalex.org/W2110762162","https://openalex.org/W2112724113","https://openalex.org/W2150427470","https://openalex.org/W2240536162","https://openalex.org/W2308827608","https://openalex.org/W2427881153","https://openalex.org/W2565466087","https://openalex.org/W2745238137","https://openalex.org/W2767493192","https://openalex.org/W2893274332","https://openalex.org/W2903461962","https://openalex.org/W2904346342","https://openalex.org/W2937274403","https://openalex.org/W2946357855","https://openalex.org/W2953247561","https://openalex.org/W2963554411","https://openalex.org/W3003635785","https://openalex.org/W3005692341","https://openalex.org/W3098561233","https://openalex.org/W3098867371","https://openalex.org/W3108706354","https://openalex.org/W3127221797","https://openalex.org/W3148008790","https://openalex.org/W6614550900","https://openalex.org/W6677031804","https://openalex.org/W6698187734","https://openalex.org/W6757010002"],"related_works":["https://openalex.org/W2504004674","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W1595229445","https://openalex.org/W2498744856","https://openalex.org/W4390482104","https://openalex.org/W322408318","https://openalex.org/W149041114","https://openalex.org/W2963177394","https://openalex.org/W1965815883"],"abstract_inverted_index":{"Change-point":[0],"analysis":[1],"is":[2,108,163],"thriving":[3],"in":[4,13,33,157],"this":[5],"Big":[6],"Data":[7],"era":[8],"to":[9,22,53,56,95,142,179,185],"address":[10],"problems":[11],"arising":[12],"many":[14],"fields":[15],"where":[16],"massive":[17],"data":[18,36,145],"sequences":[19],"are":[20],"collected":[21],"study":[23],"complicated":[24],"phenomena":[25],"over":[26],"time.":[27],"It":[28],"plays":[29],"an":[30,92,117],"important":[31],"role":[32],"processing":[34],"these":[35],"by":[37],"segmenting":[38],"a":[39,73,137,172],"long":[40],"sequence":[41,123],"into":[42],"homogeneous":[43],"parts":[44],"for":[45,68,116,140,171],"follow-up":[46],"studies.":[47],"The":[48,101,131,160],"task":[49],"requires":[50],"the":[51,88,97,148,158],"method":[52,107,150,178],"be":[54],"able":[55],"process":[57],"large":[58],"datasets":[59,181,184],"quickly":[60],"and":[61,90,182],"deal":[62],"with":[63],"various":[64,153],"types":[65,154],"of":[66,78,104,124,155],"changes":[67,156],"high-dimensional":[69],"data.":[70,130],"We":[71,175],"propose":[72],"new":[74,161],"approach":[75,162],"making":[76],"use":[77],"approximate":[79],"<inline-formula":[80,109,118,125],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[81,110,119,126],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[82,111,120,127],"notation=\"LaTeX\">$k$</tex-math></inline-formula>":[83],"-nearest":[84],"neighbor":[85],"information":[86],"from":[87],"observations,":[89],"derive":[91],"analytic":[93],"formula":[94],"control":[96],"type":[98],"I":[99],"error.":[100],"time":[102],"complexity":[103],"our":[105,177],"proposed":[106,149],"notation=\"LaTeX\">$O(dn(\\log":[112],"n+k":[113],"\\log":[114],"d)+nk^{2})$</tex-math></inline-formula>":[115],"notation=\"LaTeX\">$n$</tex-math></inline-formula>":[121],"-length":[122],"notation=\"LaTeX\">$d$</tex-math></inline-formula>":[128],"-dimensional":[129],"test":[132],"statistic":[133],"we":[134],"consider":[135],"incorporates":[136],"useful":[138],"pattern":[139],"moderate-":[141],"high-":[143],"dimensional":[144],"so":[146],"that":[147],"could":[151],"detect":[152],"sequence.":[159],"also":[164],"asymptotic":[165],"distribution":[166],"free,":[167],"facilitating":[168],"its":[169,187],"usage":[170],"broader":[173],"community.":[174],"apply":[176],"fMRI":[180],"Neuropixels":[183],"illustrate":[186],"effectiveness.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}