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Non-negative sub-tensor ensemble factorization (NsTEF) algorithm. A new incremental tensor factorization for large data sets

delete2018-03-01
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V
Vincent Vigneron *
A
Andreas Kodewitz
M
Michele Nazareth da Costa
A
Ana Maria Tomé
E
Elmar Langlang
DOI:10.1016/j.sigpro.2017.09.012delete
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Abstract

Abstract

En 中文
In this work we present a novel algorithm for nonnegative tensor factorization (NTF). Standard NTF algorithms are very restricted in the size of tensors that can be decomposed. Our algorithm overcomes this size restriction by interpreting the tensor as a set of sub-tensors and by proceeding the decomposition of sub-tensor by sub-tensor. This approach requires only one sub-tensor at once to be available in memory. (C) 2017 Elsevier B.V. All rights reserved.
Keywords:
Non-negative tensor decomposition
CANDECOMP/PARAFAC Decomposition
Matrix factorization
NTF
Incremental algorithm
Learning method
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Signal Processing cover
Signal Processing
IF:
3.6
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U
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