by Haksun Li | Apr 26, 2015 |

GLASSOFAST is the Graphical LASSO algorithm to solve the covariance selection problem. References “Sustik, M.A. and Calderhead, B., “GLASSOFAST: An efficient GLASSO implementation,” UTCS Technical Report TR-12-29, November 6, 2012.” “O. Banerjee, L. E. Ghaoui and A. d’Aspremont, “Model Selection Through Sparse Maximum Likelihood Estimation for multivariate Gaussian or Binary Data,” Journal of Machine Learning Research, 9, pp. 485-516, March 2008.”...
by Haksun Li | Apr 26, 2015 |

The covariance selection problem is formulated as this: in the variable of in , where is the sample covariance matrix, the cardinality of , i.e., the number of non-zero coefficients in . is a parameter controlling the tradeoff between the likelihood and structure. References “O. Banerjee, L. E. Ghaoui and A. d’Aspremont, “Model Selection Through Sparse Maximum Likelihood Estimation for multivariate Gaussian or Binary Data,” Journal of Machine Learning Research, 9, pp. 485-516, March 2008.” “A. d’Aspremont, “Identifying Small Mean Reverting Portfolios”, 2008.”...
by Haksun Li | Apr 26, 2015 |

by Haksun Li | Apr 26, 2015 |

by Haksun Li | Apr 26, 2015 |

## Recent Comments