• Corpus ID: 239998486

Streaming Generalized Canonical Polyadic Tensor Decompositions

@article{Phipps2021StreamingGC,
  title={Streaming Generalized Canonical Polyadic Tensor Decompositions},
  author={Eric T. Phipps and Nick P. Johnson and Tamara G. Kolda},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.14514}
}
In this paper, we develop a method which we call OnlineGCP for computing the Generalized Canonical Polyadic (GCP) tensor decomposition of streaming data. GCP differs from traditional canonical polyadic (CP) tensor decompositions as it allows for arbitrary objective functions which the CP model attempts to minimize. This approach can provide better fits and more interpretable models when the observed tensor data is strongly non-Gaussian. In the streaming case, tensor data is gradually observed… 
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Figures and Tables from this paper

GOCPT: Generalized Online Canonical Polyadic Tensor Factorization and Completion

A Generalized Online Canonical Polyadic Tensor factorization and completion framework (named GOCPT) is proposed for this general setting, where the CP structure of such dynamic tensors during the evolution is maintained.

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