Eliciting structure in data Article Swipe
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Anders Holst
,
Mohamed-Rafik Bouguelia
,
Olof Görnerup
,
Sepideh Pashami
,
Ahmad Al-Shishtawy
,
Göran Falkman
,
Alexander Karlsson
,
Alan Said
,
Juhee Bae
,
Šarūnas Girdzijauskas
,
Sławomir Nowaczyk
,
Amira Soliman
·
YOU?
·
· 2019
· Open Access
·
· OA: W2945396016
YOU?
·
· 2019
· Open Access
·
· OA: W2945396016
This paper demonstrates how to explore and visualize different types of structure in data, including clusters, anomalies, causal relations, and higher order relations. The methods are developed with the goal of being as automatic as possible and applicable to massive, streaming, and distributed data. Finally, a decentralized learning scheme is discussed, enabling finding structure in the data without collecting the data centrally.
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