Title :
Tensor decomposition of Toeplitz Jacket matrices for big data processing
Author :
Jun Li ; Yier Yan ; Wei Duan ; Sangseob Song ; Moon Ho Lee
Author_Institution :
Dept. of Electron. & Inf. Eng., Chonbuk Nat. Univ., Jeonju, South Korea
Abstract :
In this paper, we consider the tensor decomposition (TD) of Toeplitz Jacket (TJ) matrices for big data processing by using the conventional higher order singular value decomposition (HOSVD) algorithm and Tensor train (TT) decomposition. In order to use HOSVD algorithm and TT decomposition, we reshape the given matrix and make it as a tensor. Due to the property of Toeplitz matrices, we use a truncated TJ matrix in stead of given matrix to reduce the complexity of TD. The results verified that the TD of the truncated TJ matrices gains a lower complexity due to smaller size of factor matrices and core tensors.
Keywords :
Big Data; Toeplitz matrices; computational complexity; singular value decomposition; tensors; HOSVD algorithm; TT decomposition; Toeplitz jacket matrices; big data processing; complexity reduction; core tensors; factor matrices; higher order singular value decomposition; tensor decomposition; tensor train; truncated TJ matrix; Approximation methods; Big data; Complexity theory; Matrix decomposition; Singular value decomposition; Standards; Tensile stress; Tensor Decomposition (TD); Tensor train (TT); Toeplitz Jacket Matrices;
Conference_Titel :
Big Data and Smart Computing (BigComp), 2015 International Conference on
Conference_Location :
Jeju
DOI :
10.1109/35021BIGCOMP.2015.7072840
