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arXiv · 2007.10798

Randomized Online CP Decomposition

Congbo Ma·Xiaowei Yang·Hu Wang
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Abstract

CANDECOMP/PARAFAC (CP) decomposition has been widely used to deal with multi-way data. For real-time or large-scale tensors, based on the ideas of randomized-sampling CP decomposition algorithm and online CP decomposition algorithm, a novel CP decomposition algorithm called randomized online CP decomposition (ROCP) is proposed in this paper. The proposed algorithm can avoid forming full Khatri-Rao product, which leads to boost the speed largely and reduce memory usage. The experimental results on synthetic data and real-world data show the ROCP algorithm is able to cope with CP decomposition for large-scale tensors with arbitrary number of dimensions. In addition, ROCP can reduce the computing time and memory usage dramatically, especially for large-scale tensors.

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Congbo Ma, Xiaowei Yang, Hu Wang. 2020-07-21. Randomized Online CP Decomposition. https://arxiv.org/abs/2007.10798

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