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Tensor Ring Decomposition
Qibin Zhao, Guoxu Zhou, Shengli Xie +2
Tensor networks have in recent years emerged as the powerful tools for solving the large-scale optimization problems. One of the most popular tensor network is tensor train (TT) de…
Decomposition of Big Tensors With Low Multilinear Rank
Guoxu Zhou, Andrzej Cichocki, Shengli Xie
Tensor decompositions are promising tools for big data analytics as they bring multiple modes and aspects of data to a unified framework, which allows us to discover complex intern…
Tensor Decompositions for Signal Processing Applications From Two-way to Multiway Component Analysis
A. Cichocki, D. Mandic, A-H. Phan +4
The widespread use of multi-sensor technology and the emergence of big datasets has highlighted the limitations of standard flat-view matrix models and the necessity to move toward…
Accelerated Canonical Polyadic Decomposition by Using Mode Reduction
Guoxu Zhou, Andrzej Cichocki, Shengli Xie
Canonical Polyadic (or CANDECOMP/PARAFAC, CP) decompositions (CPD) are widely applied to analyze high order tensors. Existing CPD methods use alternating least square (ALS) iterati…