Corpus ID: 14520283

Sparse Covariance Selection via Robust Maximum Likelihood Estimation

@article{Banerjee2005SparseCS,
  title={Sparse Covariance Selection via Robust Maximum Likelihood Estimation},
  author={Onureena Banerjee and A. d'Aspremont and L. Ghaoui},
  journal={ArXiv},
  year={2005},
  volume={abs/cs/0506023}
}

Onureena Banerjee, A. d'Aspremont, L. Ghaoui

Published 2005

Computer Science, Mathematics

ArXiv

We address a problem of covariance selection, where we seek a trade-off between a high likelihood against the number of non-zero elements in the inverse covariance matrix. We solve a maximum likelihood problem with a penalty term given by the sum of absolute values of the elements of the inverse covariance matrix, and allow for imposing bounds on the condition number of the solution. The problem is directly amenable to now standard interiorpoint algorithms for convex optimization, but remains… CONTINUE READING

View PDF on arXiv

Save to Library

Create Alert

Cite

Launch Research Feed