Fast alternating LS algorithms for high order CANDECOMP/PARAFAC tensor factorizations

Anh Huy Phan, Petr Tichavský, Andrzej Cichocki

Research output: Contribution to journalArticlepeer-review

94 Citations (Scopus)

Abstract

CANDECOMP/PARAFAC (CP) has found numerous applications in wide variety of areas such as in chemometrics, telecommunication, data mining, neuroscience, separated representations. For an order-N tensor, most CP algorithms can be computationally demanding due to computation of gradients which are related to products between tensor unfoldings and Khatri-Rao products of all factor matrices except one. These products have the largest workload in most CP algorithms. In this paper, we propose a fast method to deal with this issue. The method also reduces the extra memory requirements of CP algorithms. As a result, we can accelerate the standard alternating CP algorithms 20-30 times for order-5 and order-6 tensors, and even higher ratios can be obtained for higher order tensors (e.g., N≥ 10). The proposed method is more efficient than the state-of-the-art ALS algorithm which operates two modes at a time (ALSo2) in the Eigenvector PLS toolbox, especially for tensors with order N≥ 5 and high rank.

Original languageEnglish
Article number6544287
Pages (from-to)4834-4846
Number of pages13
JournalIEEE Transactions on Signal Processing
Volume61
Issue number19
DOIs
Publication statusPublished - 2013
Externally publishedYes

Keywords

  • ALS
  • CANDECOMP/PARAFAC (CP)
  • Canonical decomposition
  • Gradient
  • Tensor factorization

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