{"id":"https://openalex.org/W4323782874","doi":"https://doi.org/10.1007/978-3-031-25891-6_21","title":"Robust PCA for\u00a0Anomaly Detection and\u00a0Data Imputation in\u00a0Seasonal Time Series","display_name":"Robust PCA for\u00a0Anomaly Detection and\u00a0Data Imputation in\u00a0Seasonal Time Series","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4323782874","doi":"https://doi.org/10.1007/978-3-031-25891-6_21"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-031-25891-6_21","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-031-25891-6_21","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5086945312","display_name":"H\u00f4ng-Lan Botterman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"H\u00f4ng-Lan Botterman","raw_affiliation_strings":["Quantmetry, 52 rue d\u2019Anjou, 75008, Paris, France","Quantmetry, 52 rue d'Anjou, 75008, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Quantmetry, 52 rue d\u2019Anjou, 75008, Paris, France","institution_ids":[]},{"raw_affiliation_string":"Quantmetry, 52 rue d'Anjou, 75008, Paris, France","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057145134","display_name":"Julien Roussel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Julien Roussel","raw_affiliation_strings":["Quantmetry, 52 rue d\u2019Anjou, 75008, Paris, France","Quantmetry, 52 rue d'Anjou, 75008, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Quantmetry, 52 rue d\u2019Anjou, 75008, Paris, France","institution_ids":[]},{"raw_affiliation_string":"Quantmetry, 52 rue d'Anjou, 75008, Paris, France","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074167089","display_name":"Thomas Morzadec","orcid":"https://orcid.org/0000-0003-1631-5421"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thomas Morzadec","raw_affiliation_strings":["Quantmetry, 52 rue d\u2019Anjou, 75008, Paris, France","Quantmetry, 52 rue d'Anjou, 75008, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Quantmetry, 52 rue d\u2019Anjou, 75008, Paris, France","institution_ids":[]},{"raw_affiliation_string":"Quantmetry, 52 rue d'Anjou, 75008, Paris, France","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103780035","display_name":"Ali Jabbari","orcid":"https://orcid.org/0000-0003-3075-8616"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ali Jabbari","raw_affiliation_strings":["Quantmetry, 52 rue d\u2019Anjou, 75008, Paris, France","Quantmetry, 52 rue d'Anjou, 75008, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Quantmetry, 52 rue d\u2019Anjou, 75008, Paris, France","institution_ids":[]},{"raw_affiliation_string":"Quantmetry, 52 rue d'Anjou, 75008, Paris, France","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034657220","display_name":"Nicolas J-B. Brunel","orcid":"https://orcid.org/0000-0002-2840-8484"},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4210097372","display_name":"\u00c9cole Nationale Sup\u00e9rieure d\u2019Informatique pour l\u2019Industrie et l\u2019Entreprise","ror":"https://ror.org/00tx98v53","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210097372"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Nicolas Brunel","raw_affiliation_strings":["LaMME, ENSIIE, Universit\u00e9 Paris Saclay, 1 square de la R\u00e9sistance, 91025, Evry Cedex, France","Quantmetry, 52 rue d\u2019Anjou, 75008, Paris, France"],"raw_orcid":"https://orcid.org/0000-0002-2840-8484","affiliations":[{"raw_affiliation_string":"LaMME, ENSIIE, Universit\u00e9 Paris Saclay, 1 square de la R\u00e9sistance, 91025, Evry Cedex, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I4210097372"]},{"raw_affiliation_string":"Quantmetry, 52 rue d\u2019Anjou, 75008, Paris, France","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5034657220"],"corresponding_institution_ids":["https://openalex.org/I277688954","https://openalex.org/I4210097372"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":1.8851,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.82708646,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"281","last_page":"295"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9987000226974487,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9977999925613403,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9936000108718872,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8307246565818787},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.742478609085083},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6543118953704834},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6175031661987305},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6061246395111084},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5572472810745239},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.5355280637741089},{"id":"https://openalex.org/keywords/streaming-data","display_name":"Streaming data","score":0.5079756379127502},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.4697585105895996},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.44979146122932434},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.44236335158348083},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4244352877140045},{"id":"https://openalex.org/keywords/sparse-pca","display_name":"Sparse PCA","score":0.4203081727027893},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3632890284061432},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.2991935610771179},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2628993093967438},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09336751699447632}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8307246565818787},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.742478609085083},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6543118953704834},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6175031661987305},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6061246395111084},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5572472810745239},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.5355280637741089},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.5079756379127502},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.4697585105895996},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.44979146122932434},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.44236335158348083},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4244352877140045},{"id":"https://openalex.org/C24252448","wikidata":"https://www.wikidata.org/wiki/Q7573786","display_name":"Sparse PCA","level":3,"score":0.4203081727027893},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3632890284061432},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.2991935610771179},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2628993093967438},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09336751699447632},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"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:10.1007/978-3-031-25891-6_21","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-031-25891-6_21","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1926570426","https://openalex.org/W1967336819","https://openalex.org/W1974315654","https://openalex.org/W1975189025","https://openalex.org/W1987551552","https://openalex.org/W2001178002","https://openalex.org/W2004026774","https://openalex.org/W2125291718","https://openalex.org/W2145962650","https://openalex.org/W2147152072","https://openalex.org/W2149532724","https://openalex.org/W2168955340","https://openalex.org/W2295124130","https://openalex.org/W2588589522","https://openalex.org/W2611328865","https://openalex.org/W2762833822","https://openalex.org/W2886248458","https://openalex.org/W2887843685","https://openalex.org/W2962834831","https://openalex.org/W3122732016","https://openalex.org/W3155567600","https://openalex.org/W3156676741","https://openalex.org/W4232442502","https://openalex.org/W4292363360","https://openalex.org/W6600376255","https://openalex.org/W6600407735","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W2302215559","https://openalex.org/W2463344124","https://openalex.org/W107071865","https://openalex.org/W2145962650","https://openalex.org/W4283792950","https://openalex.org/W2951443864","https://openalex.org/W2791609404","https://openalex.org/W2565806648","https://openalex.org/W2405786797","https://openalex.org/W2115608034"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"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"}
