Error Analysis for Matrix Elastic-Net Regularization Algorithms

  title={Error Analysis for Matrix Elastic-Net Regularization Algorithms},
  author={Hong Li and Na Chen and Luoqing Li},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
Elastic-net regularization is a successful approach in statistical modeling. It can avoid large variations which occur in estimating complex models. In this paper, elastic-net regularization is extended to a more general setting, the matrix recovery (matrix completion) setting. Based on a combination of the nuclear-norm minimization and the Frobenius-norm minimization, we consider the matrix elastic-net (MEN) regularization algorithm, which is an analog to the elastic-net regularization scheme… CONTINUE READING