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 proceedings sparse inverse covariance estimation

Sparse Inverse Covariance Estimation with Calibration

Neural Information Processing Systems

We propose a semiparametric procedure for estimating high dimensional sparse inverse covariance matrix. Our method, named ALICE, is applicable to the elliptical family. Computationally, we develop an efficient dual inexact iterative projection (${\rm D_2}$P) algorithm based on the alternating direction method of multipliers (ADMM). Theoretically, we prove that the ALICE estimator achieves the parametric rate of convergence in both parameter estimation and model selection.

  artificial intelligence, machine learning, proceedings sparse inverse covariance estimation, (7 more...)
  Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.62)

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