{"id":"https://openalex.org/W4385489438","doi":"https://doi.org/10.1145/3594315.3594655","title":"Multivariate Time Series Anomaly Detection in a Regularization Perspective","display_name":"Multivariate Time Series Anomaly Detection in a Regularization Perspective","publication_year":2023,"publication_date":"2023-03-17","ids":{"openalex":"https://openalex.org/W4385489438","doi":"https://doi.org/10.1145/3594315.3594655"},"language":"en","primary_location":{"id":"doi:10.1145/3594315.3594655","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3594315.3594655","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 9th International Conference on Computing and Artificial Intelligence","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":null,"display_name":"Qi Guo","orcid":"https://orcid.org/0009-0000-1992-5730"},"institutions":[{"id":"https://openalex.org/I2800372957","display_name":"China Electronics Technology Group Corporation","ror":"https://ror.org/0098hst83","country_code":"CN","type":"company","lineage":["https://openalex.org/I2800372957"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qi Guo","raw_affiliation_strings":["54th Research Institute of China Electronics Technology Group Corporation, China"],"raw_orcid":"https://orcid.org/0009-0000-1992-5730","affiliations":[{"raw_affiliation_string":"54th Research Institute of China Electronics Technology Group Corporation, China","institution_ids":["https://openalex.org/I2800372957"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067954263","display_name":"Jinwei Zhang -","orcid":"https://orcid.org/0009-0001-0650-5611"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinwei Zhang","raw_affiliation_strings":["Xidian University, China"],"raw_orcid":"https://orcid.org/0009-0001-0650-5611","affiliations":[{"raw_affiliation_string":"Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101420438","display_name":"Yong Chen","orcid":"https://orcid.org/0009-0007-8129-5363"},"institutions":[{"id":"https://openalex.org/I2800372957","display_name":"China Electronics Technology Group Corporation","ror":"https://ror.org/0098hst83","country_code":"CN","type":"company","lineage":["https://openalex.org/I2800372957"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Chen","raw_affiliation_strings":["54th Research Institute of China Electronics Technology Group Corporation, China"],"raw_orcid":"https://orcid.org/0009-0007-8129-5363","affiliations":[{"raw_affiliation_string":"54th Research Institute of China Electronics Technology Group Corporation, China","institution_ids":["https://openalex.org/I2800372957"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022334584","display_name":"Ruochen Liu","orcid":"https://orcid.org/0000-0002-0502-4074"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruochen Liu","raw_affiliation_strings":["Xidian University, China"],"raw_orcid":"https://orcid.org/0000-0002-0502-4074","affiliations":[{"raw_affiliation_string":"Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2800372957"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08761175,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"279","last_page":"287"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9930999875068665,"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/anomaly-detection","display_name":"Anomaly detection","score":0.7159285545349121},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6894777417182922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5811155438423157},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5774002075195312},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5587756633758545},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5584335327148438},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5220394134521484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4296382963657379},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37054431438446045},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29726171493530273},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.0843789279460907}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7159285545349121},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6894777417182922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5811155438423157},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5774002075195312},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5587756633758545},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5584335327148438},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5220394134521484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4296382963657379},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37054431438446045},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29726171493530273},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0843789279460907},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3594315.3594655","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3594315.3594655","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 9th International Conference on Computing and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1968527334","https://openalex.org/W2296719434","https://openalex.org/W2407991977","https://openalex.org/W2743617586","https://openalex.org/W2766149053","https://openalex.org/W2768947629","https://openalex.org/W2773548424","https://openalex.org/W2785362611","https://openalex.org/W2786827964","https://openalex.org/W2896333468","https://openalex.org/W2911200746","https://openalex.org/W2948517885","https://openalex.org/W2950361482","https://openalex.org/W2964321699","https://openalex.org/W3004999940","https://openalex.org/W3081497074","https://openalex.org/W3098957257","https://openalex.org/W3101969501","https://openalex.org/W3105931142","https://openalex.org/W3106543020","https://openalex.org/W3170937175","https://openalex.org/W3170981104","https://openalex.org/W3176085787","https://openalex.org/W6720006811"],"related_works":["https://openalex.org/W2406638334","https://openalex.org/W1991765889","https://openalex.org/W1990068454","https://openalex.org/W2472172556","https://openalex.org/W1919101720","https://openalex.org/W1570805059","https://openalex.org/W2118640767","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Real-world":[0],"scenarios":[1],"such":[2],"as":[3],"Internet,":[4],"industrial":[5],"equipment":[6],"and":[7,119],"finance":[8],"field":[9],"generate":[10],"a":[11,30,42,69,83,110],"large":[12],"number":[13],"of":[14,29,63],"multivariate":[15,37],"time":[16,20,38],"series":[17,39],"all":[18],"the":[19,26,36,60,94,98],"which":[21],"are":[22],"important":[23,55],"for":[24,93],"describing":[25],"operational":[27],"state":[28],"system.":[31],"Therefore,":[32],"anomaly":[33],"detection":[34],"on":[35,128],"has":[40],"become":[41],"hot":[43],"topic":[44],"today.":[45],"How":[46],"to":[47,50,88,106,116],"utilize":[48],"regularization":[49,100],"eliminate":[51],"overfitting":[52],"is":[53,78,104,114],"an":[54],"issue":[56],"since":[57],"it":[58],"inhibits":[59],"representative":[61,91],"power":[62],"existing":[64],"models.":[65],"In":[66],"this":[67],"paper,":[68],"reconstruction":[70,86,118],"model":[71,123],"called":[72],"Autoregressive":[73],"Graph":[74],"Adversarial":[75],"Network":[76],"(ARGAN)":[77],"proposed.":[79],"First,":[80],"we":[81],"develop":[82],"latent":[84],"space":[85],"strategy":[87,113],"guarantee":[89],"ARGAN\u2019s":[90],"ability":[92],"key":[95],"features.":[96],"Then,":[97],"autoregressive":[99],"using":[101],"temporal":[102],"dependency":[103],"proposed":[105,122],"inhibit":[107],"overfitting.":[108],"Finally,":[109],"regularized":[111],"annealing":[112],"designed":[115],"balance":[117],"regularization.":[120],"The":[121],"can":[124],"achieve":[125],"better":[126],"performance":[127],"four":[129],"real-world":[130],"datasets":[131],"compared":[132],"with":[133],"other":[134],"six":[135],"algorithms.":[136]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}