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Analyse de grandes données tensorielles couplées

Abstract : Tensor data analysis is presently one of the hot topics in signal processing. New measurement tools allow huge amount of multi-variate complementary data to be collected on the same physical phenomenon, a property very well exploited by tensor algebra. In this paper, we treat the big data problem when tensorial data are coupled along one factor. A joint compression scheme and new coupled decomposition algorithms are introduced and demonstrated on synthetic data.
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https://hal.archives-ouvertes.fr/hal-01135090
Contributor : Jeremy E. Cohen <>
Submitted on : Tuesday, March 24, 2015 - 4:38:05 PM
Last modification on : Thursday, November 19, 2020 - 1:01:15 PM

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Jérémy Cohen, Rodrigo Cabral Farias, Pierre Comon. Analyse de grandes données tensorielles couplées. XXVème colloque GRETSI (GRETSI 2015), Sep 2015, Lyon, France. ⟨hal-01135090⟩

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