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This paper presents DECO (Dresden Enron COrpus), a dataset of spreadsheet files, annotated on the basis of layout and contents. It comprises of 1,165 files, extracted from the Enron corpus. Three different annotators (judges) assigned layout roles (e
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https://tud.qucosa.de/id/qucosa%3A82977
https://tud.qucosa.de/api/qucosa%3A82977/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82977/attachment/ATT-0/
Autor:
Rehak, Josephine
The discovery of causal relations via interventions has proven to be simple when only one observed variable is affected or unaffected. However, in a multivariate setting, it is likely that more than one variable is affected by the intervention. Thus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e6f9fef5f987a6383ad714a36b1c2d52
Autor:
Rehak, Josephine
Learning the skill to discover causal relations and to make use of them is said to be an essential step in human intelligence [43, 31] and potentially also in machine intelligence [28, 38]. The domain of causal discovery tackles the challenge of iden
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1abd26c00e9626693a0bed4fa36c30ad
Autor:
Rehak, Josephine
Causal Discovery has become an area of high interest for researchers. It haslead to great advances in medicine, in the social sciences and in genetics. Butup til now, it is hardly used to identify causal relations in technical systems.This paper pres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::930b2cb07807429af9e83660bc6ba052
https://publikationen.bibliothek.kit.edu/1000135218/120370791
https://publikationen.bibliothek.kit.edu/1000135218/120370791