High-dimensional Models
Publications
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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).
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.
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 Group-Sparse Regularization 2011
A. Jalali, P. Ravikumar, V. Vasuki, and S. Sanghavi, In International Conference on AI and Statistics (AISTATS) 2011.
A Dirty Model for Multi-task Learning 2010
A. Jalali, P. Ravikumar, S. Sanghavi, and C. Ruan, In Neural Information Processing Systems 2010.
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.
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.
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.