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Matrix Polynomial Predictive Model: A New Approach to Accelerating the PARAFAC Decomposition
Alternating least squares (ALS) and its variations are the most commonly used algorithms for the PARAFAC decomposition of a tensor. However, it is still troubled for one how to accelerate the ALS algorithm with the reduced computational complexity. In this paper, a new acceleration method for the ALS with a matrix polynomial predictive model (MPPM) is proposed. In the MPPM, a matrix-valued function is first approximated by a matrix polynomial. It is shown that the future value of the functiondoi:10.1109/access.2019.2927440 fatcat:3gesfcmjlvajve6xnfksbhpiya