Tensor Decomposition for Signal Processing and Machine Learning

Tensors or multiway arrays are functions of three or more indices (i, j, k, . . . )-similar to matrices (two-way arrays), which are functions of two indices (r, c) for (row, column). Tensors have a rich history, stretching over almost a century, and touching upon numerous disciplines; but they have...

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Bibliographic Details
Published in:	IEEE transactions on signal processing Vol. 65; no. 13; pp. 3551 - 3582
Main Authors:	Sidiropoulos, Nicholas D., De Lathauwer, Lieven, Xiao Fu, Kejun Huang, Papalexakis, Evangelos E., Faloutsos, Christos
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.07.2017 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms alternating direction method of multipliers alternating optimization Arrays canonical polyadic decomposition (CPD) classification collaborative filtering communications Cramér–Rao bound Data analysis Data mining Decomposition Gauss–Newton gradient descent harmonic retrieval higher-order singular value decomposition (HOSVD) Machine learning Matrix algebra Matrix decomposition mixture modeling multilinear singular value decomposition (MLSVD) NP-hard problems Optimization parallel factor analysis (PARAFAC) rank Signal processing Signal processing algorithms source separation speech separation Statistical analysis stochastic gradient subspace learning Tensile stress Tensor decomposition tensor factorization Tensors topic modeling Tucker model Tutorials uniqueness
ISSN:	1053-587X, 1941-0476
Online Access:	Get full text
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