Partitioned Hierarchical alternating least squares algorithm for CP tensor decomposition

Anh Huy Phan; Petr Tichavský; Andrzej Cichocki

ICASSP 2017accepted0 citations

Partitioned Hierarchical alternating least squares algorithm for CP tensor decomposition

Anh Huy Phan, Petr Tichavský, Andrzej Cichocki

Abstract

Canonical polyadic decomposition (CPD), also known as PARAFAC, is a representation of a given tensor as a sum of rank-one tensors. Traditional method for accomplishing CPD is the alternating least squares (ALS) algorithm. This algorithm is easy to implement with very low computational complexity per iteration. A disadvantage is that in difficult scenarios, where factor matrices in the decomposition contain nearly collinear columns, the number of iterations needed to achieve convergence might be very large. In this paper, we propose a modification of the algorithm which has similar complexity per iteration as ALS, but in difficult scenarios it needs a significantly lower number of iterations.

BibTeX

@inproceedings{icassp2017_partitionedhiera,
  title = {Partitioned Hierarchical alternating least squares algorithm for CP tensor decomposition},
  author = {Anh Huy Phan and Petr Tichavský and Andrzej Cichocki},
  booktitle = {ICASSP 2017},
  year = {2017}
}