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In this work we propose algorithms for detecting multivariate correlations in static and streaming data. Our algorithms, which rely on novel theoretical results, support two different correlation measures, and allow for additional constraints. Our extensive experimental evaluation examines the properties of our solution and demonstrates that our algorithms outperform the state-of-the-art, typically by an order of magnitude.\n          <\/jats:p>","DOI":"10.14778\/3514061.3514072","type":"journal-article","created":{"date-parts":[[2022,6,22]],"date-time":"2022-06-22T22:26:10Z","timestamp":1655936770000},"page":"1266-1278","source":"Crossref","is-referenced-by-count":3,"title":["Multivariate correlations discovery in static and streaming data"],"prefix":"10.14778","volume":"15","author":[{"given":"Koen","family":"Minartz","sequence":"first","affiliation":[{"name":"Eindhoven University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jens E.","family":"d'Hondt","sequence":"additional","affiliation":[{"name":"Eindhoven University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Odysseas","family":"Papapetrou","sequence":"additional","affiliation":[{"name":"Eindhoven University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,6,22]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098099"},{"key":"e_1_2_1_2_1","first-page":"1798","article-title":"Mining Novel Multivariate Relationships in Time Series Data Using Correlation Networks","volume":"32","author":"Agrawal Saurabh","year":"2020","unstructured":"Saurabh Agrawal , Michael Steinbach , Daniel Boley , Snigdhansu Chatterjee , Gowtham Atluri , Anh The Dang , Stefan Liess , and Vipin Kumar . 2020 . 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