Tensor Completion by Alternating Minimization under the Tensor Train (TT) Model

@article{Wang2016TensorCB,
  title={Tensor Completion by Alternating Minimization under the Tensor Train (TT) Model},
  author={Wenqi Wang and Vaneet Aggarwal and Shuchin Aeron},
  journal={CoRR},
  year={2016},
  volume={abs/1609.05587}
}
Using the matrix product state (MPS) representation of tensor train decompositions, in this paper we propose a tensor completion algorithm which alternates over the matrices (tensors) in the MPS representation. This development is motivated in part by the success of matrix completion algorithms which alternate over the (low-rank) factors. We comment on the computational complexity of the proposed algorithm and numerically compare it with existing methods employing low rank tensor train… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 16 references

A Practical Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States

  • Roman Orus
  • Annals Phys., vol. 349, pp. 117–158, 2014.
  • 2014
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Kilmer , “ 5 d seismic data completion and denoising using a novel class of tensor decompositions

  • Gregory Ely, Shuchin Aeron, E Misha
  • 2015

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