Conditional Random Fields via Univariate Exponential Families | 2013 |

Eunho Yang, Pradeep Ravikumar, Genevera Allen and Zhandong Liu, In *Advances in Neural Information Processing Systems (NIPS)* 2013. |

On Poisson Graphical Models | 2013 |

Eunho Yang, Pradeep Ravikumar, Genevera Allen and Zhandong Liu, In *Advances in Neural Information Processing Systems (NIPS)* 2013. |

A Divide-and-Conquer Procedure for Sparse Inverse Covariance Estimation | 2012 |

Cho-Jui Hsieh, Inderjit Dhillon, Pradeep Ravikumar, and Arindam Banerjee, *NIPS* (2012). |

Graphical Models via Generalized Linear Models | 2012 |

Eunho Yang, Pradeep Ravikumar, Genevera Allen, and Zhandong Liu, *NIPS* (2012). |

High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods | 2012 |

Christopher Johnson, Ali Jalali, and Pradeep Ravikumar, In *International Conference on AI and Statistics (AISTATS)* 2012. |

High-dimensional covariance estimation by minimizing l1-penalized log-determinant divergence | 2011 |

P. Ravikumar, M. J. Wainwright, G. Raskutti, and B. Yu, *Electronic Journal of Statistics*, Vol. 5 (2011), pp. 935-980. |

On Learning Discrete Graphical Models using Greedy Methods | 2011 |

Ali Jalali, Christopher Johnson, and Pradeep Ravikumar, In *Neural Information Processing Systems* 2011. |

On Learning Discrete Graphical Models using Group-Sparse Regularization | 2011 |

A. Jalali, P. Ravikumar, V. Vasuki, and S. Sanghavi, In *International Conference on AI and Statistics (AISTATS)* 2011. |

On the Use of Variational Inference for Learning Discrete Graphical Models | 2011 |

Eunho Yang and Pradeep Ravikumar, In *International Conference on Machine learning (ICML)* 2011. |

Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation | 2011 |

C.-J. Hsieh, M. Sustik, I. Dhillon, and P. Ravikumar, In *Neural Information Processing Systems* 2011. |

Message-passing for graph-structured linear programs: proximal methods and rounding schemes | 2010 |

P. Ravikumar, A. Agarwal, and M. J. Wainwright, *Journal of Machine Learning Research (JMLR)*, Vol. 11 (2010), pp. 1043-1080. |

Message-passing for graph-structured linear programs: Proximal projections, convergence and rounding schemes | 2008 |

P. Ravikumar, A. Agarwal, and M. J. Wainwright, In *International Conference on Machine learning (ICML)* 2008. |

Model selection in Gaussian graphical models: High-dimensional consistency of l1-regularized MLE | 2008 |

P. Ravikumar, M. J. Wainwright, G. Raskutti, and B. Yu, In *Neural Information Processing Systems* 2008. |

Approximate inference, structure learning and feature estimation in Markov random fields | 2007 |

P. Ravikumar, *Technical Report CMU-ML-07-115, Ph.D. Thesis, Carnegie Mellon University* (2007). |

High-dimensional graphical model selection using l1-regularized logistic regression | 2006 |

M. J. Wainwright, P. Ravikumar, and J. Lafferty, In *Neural Information Processing Systems* 2006. |

Preconditioner approximations for probabilistic graphical models | 2006 |

P. Ravikumar and J. Lafferty, In *Neural Information Processing Systems*, pp. 1113-1120 2006. |

Quadratic programming relaxations for metric labeling and Markov random field MAP estimation | 2006 |

P. Ravikumar and J. Lafferty, In *International Conference on Machine learning (ICML)*, pp. 737-744 2006. |

A Hierarchical Graphical Model for Record Linkage | 2004 |

P. Ravikumar and W. W. Cohen, In *Uncertainty in Artificial Intelligence (UAI)*, pp. 454-461 2004. |

Variational Chernoff bounds for graphical models | 2004 |

P. Ravikumar and J. Lafferty, In *Uncertainty in Artificial Intelligence (UAI)*, pp. 462-469 2004. |