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. |

Dirty Statistical Models | 2013 |

Eunho Yang and Pradeep Ravikumar, *Advances in Neural Information Processing Systems (NIPS)* (2013). |

Human Boosting | 2013 |

Harsh Pareek and Pradeep Ravikumar, *ICML* (2013). |

On Poisson Graphical Models | 2013 |

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

On Robust Estimation of High Dimensional Generalized Linear Models | 2013 |

Eunho Yang, Ambuj Tewari and Pradeep Ravikumar, In *International Joint Conference on Artificial Intelligence (IJCAI) * 2013. |

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

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

A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers | 2012 |

S. Negahban, P. Ravikumar, M. J. Wainwright, and B. Yu, *Statistical Science* (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. |

Information-theoretic lower bounds on the oracle complexity of convex optimization | 2012 |

A. Agarwal, P. Bartlett, P. Ravikumar, and M. Wainwright, *IEEE Transactions on Information Theory*, Vol. 58, 5 (2012), pp. 3235-3249. |

Perturbation based Large Margin Approach for Ranking | 2012 |

Eunho Yang, Ambuj Tewari and Pradeep Ravikumar, In *International Conference on Artificial Intelligence and Statistics (AISTATS)* 2012. |

Encoding and Decoding V1 fMRI Responses to Natural Images with Sparse Nonparametric Models | 2011 |

V. Vu, P. Ravikumar, T. Naselaris, K. Kay, J. Gallant, and B. Yu, *Annals of Applied Statistics* (2011), pp. 1159-1182. |

Greedy Algorithms for Structurally Constrained High Dimensional Problems | 2011 |

A. Tewari, P. Ravikumar, and I. Dhillon, In *Neural Information Processing Systems* 2011. |

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. |

Nearest Neighbor based Greedy Coordinate Descent | 2011 |

I. Dhillon, P. Ravikumar, and A. Tewari, In *Neural Information Processing Systems* 2011. |

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 NDCG Consistency of Listwise Ranking Methods | 2011 |

Pradeep Ravikumar, Ambuj Tewari and Eunho Yang, *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. |

A Dirty Model for Multi-task Learning | 2010 |

A. Jalali, P. Ravikumar, S. Sanghavi, and C. Ruan, In *Neural Information Processing Systems* 2010. |

Information-theoretic lower bounds on the oracle complexity of sparse convex optimization | 2010 |

A. Agarwal, P. Bartlett, P. Ravikumar, and M. Wainwright, In *International Workshop on Optimization for Machine Learning (OPT)* 2010. |

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. |

A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers | 2009 |

S. Negahban, P. Ravikumar, M. J. Wainwright, and B. Yu, In *Neural Information Processing Systems* 2009. |

Information-theoretic lower bounds on the oracle complexity of convex optimization | 2009 |

A. Agarwal, P. Bartlett, P. Ravikumar, and M. Wainwright, In *Neural Information Processing Systems* 2009. |

Sparse Additive Models | 2009 |

P. Ravikumar, J. Lafferty, H. Liu, and L. Wasserman, *Journal of the Royal Statistical Society: Series B (Statistical Methodology) (JRSSB)*, Vol. 71, 5 (2009), pp. 1009-1030. |

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. |

Nonparametric sparse hierarchical models describe V1 fmri responses to natural images | 2008 |

P. Ravikumar, V. Vu, B. Yu, T. Naselaris, K. Kay, and J. Gallant, 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). |

SpAM: sparse additive models | 2007 |

P. Ravikumar, J. Lafferty, H. Liu, and L. Wasserman, In *Neural Information Processing Systems* 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. |

Comments: The Sensitivity of Economic Statistics to Coding Errors in Personal Identifiers | 2005 |

W. W. Cohen, S. Fienberg, and P. Ravikumar, *Journal of Business and Economic Statistics*, Vol. 23, 2 (2005), pp. 160-162. |

A Hierarchical Graphical Model for Record Linkage | 2004 |

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

A Secure Protocol for Computing String Distance Metrics | 2004 |

P. Ravikumar, W. W. Cohen, and S. E. Fienberg, In *In IEEE International Conference on Data Mining (ICDM) 04, Workshop on Privacy and Security Aspects of Data Mining* 2004. |

Variational Chernoff bounds for graphical models | 2004 |

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

A Comparison of String Distance Metrics for Name-Matching Tasks | 2003 |

W. W. Cohen, P. Ravikumar, and S. Fienberg, In *In International Joint Conference on Artificial Intelligence (IJCAI) 18, Workshop on Information Integration on the Web* 2003. |

A Comparison of String Metrics for Matching Names and Records | 2003 |

W. W. Cohen, P. Ravikumar, and S. Fienberg, In *International Conference on Knowledge Discovery and Data Mining (KDD) 09, Workshop on Data Cleaning, Record Linkage, and Object Consolidation* 2003. |

Adaptive Name-Matching in Information Integration | 2003 |

Mikhail Bilenko, William W. Cohen, Stephen Fienberg, Raymond J. Mooney, and Pradeep Ravikumar, *IEEE Intelligent Systems*, Vol. 18, 5 (2003), pp. 16-23. |