Efficient Sparse Low-Rank Tensor Completion Using the Frank-Wolfe Algorithm

@inproceedings{Guo2017EfficientSL,
  title={Efficient Sparse Low-Rank Tensor Completion Using the Frank-Wolfe Algorithm},
  author={Xiawei Guo and Quanming Yao and James T. Kwok},
  booktitle={AAAI},
  year={2017}
}
Most tensor problems are NP-hard, and low-rank tensor completion is much more difficult than low-rank matrix completion. In this paper, we propose a time and spaceefficient low-rank tensor completion algorithm by using the scaled latent nuclear norm for regularization and the FrankWolfe (FW) algorithm for optimization. We show that all the steps can be performed efficiently. In particular, FW’s linear subproblem has a closed-form solution which can be obtained from rank-one SVD. By utilizing… CONTINUE READING