Pradeep Ravikumar
Faculty
Homepage:
http://www.cs.utexas.edu/~pradeepr/
Publications
     [Expand to show all 37][Minimize]
Human Boosting 2013
Harsh Pareek and Pradeep Ravikumar
A Divide-and-Conquer Procedure for Sparse Inverse Covariance Estimation 2012
Cho-Jui Hsieh, Inderjit Dhillon, Pradeep Ravikumar, and Arindam Banerjee
A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers 2012
S. Negahban, P. Ravikumar, M. J. Wainwright, and B. Yu
Graphical Models via Generalized Linear Models 2012
Eunho Yang, Pradeep Ravikumar, Genevera Allen, and Zhandong Liu
High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods 2012
Christopher Johnson, Ali Jalali, and Pradeep Ravikumar
Information-theoretic lower bounds on the oracle complexity of convex optimization 2012
A. Agarwal, P. Bartlett, P. Ravikumar, and M. Wainwright
Perturbation based Large Margin Approach for Ranking 2012
E. Yang, A. Tewari, and P. Ravikumar
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
Greedy Algorithms for Structurally Constrained High Dimensional Problems 2011
A. Tewari, P. Ravikumar, and I. Dhillon
High-dimensional covariance estimation by minimizing l1-penalized log-determinant divergence 2011
P. Ravikumar, M. J. Wainwright, G. Raskutti, and B. Yu
Nearest Neighbor based Greedy Coordinate Descent 2011
I. Dhillon, P. Ravikumar, and A. Tewari
On Learning Discrete Graphical Models using Greedy Methods 2011
Ali Jalali, Christopher Johnson, and Pradeep Ravikumar
On Learning Discrete Graphical Models using Group-Sparse Regularization 2011
A. Jalali, P. Ravikumar, V. Vasuki, and S. Sanghavi
On NDCG Consistency of Listwise Ranking Methods 2011
P. Ravikumar, A. Tewari, and E. Yang
On the Use of Variational Inference for Learning Discrete Graphical Models 2011
E. Yang and P. Ravikumar
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation 2011
C.-J. Hsieh, M. Sustik, I. Dhillon, and P. Ravikumar
A Dirty Model for Multi-task Learning 2010
A. Jalali, P. Ravikumar, S. Sanghavi, and C. Ruan
Information-theoretic lower bounds on the oracle complexity of sparse convex optimization 2010
A. Agarwal, P. Bartlett, P. Ravikumar, and M. Wainwright
Message-passing for graph-structured linear programs: proximal methods and rounding schemes 2010
P. Ravikumar, A. Agarwal, and M. J. Wainwright
A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers 2009
S. Negahban, P. Ravikumar, M. J. Wainwright, and B. Yu
Information-theoretic lower bounds on the oracle complexity of convex optimization 2009
A. Agarwal, P. Bartlett, P. Ravikumar, and M. Wainwright
Sparse Additive Models 2009
P. Ravikumar, J. Lafferty, H. Liu, and L. Wasserman
Message-passing for graph-structured linear programs: Proximal projections, convergence and rounding schemes 2008
P. Ravikumar, A. Agarwal, and M. J. Wainwright
Model selection in Gaussian graphical models: High-dimensional consistency of l1-regularized MLE 2008
P. Ravikumar, M. J. Wainwright, G. Raskutti, and B. Yu
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
Approximate inference, structure learning and feature estimation in Markov random fields 2007
P. Ravikumar
SpAM: sparse additive models 2007
P. Ravikumar, J. Lafferty, H. Liu, and L. Wasserman
High-dimensional graphical model selection using l1-regularized logistic regression 2006
M. J. Wainwright, P. Ravikumar, and J. Lafferty
Preconditioner approximations for probabilistic graphical models 2006
P. Ravikumar and J. Lafferty
Quadratic programming relaxations for metric labeling and Markov random field MAP estimation 2006
P. Ravikumar and J. Lafferty
Comments: The Sensitivity of Economic Statistics to Coding Errors in Personal Identifiers 2005
W. W. Cohen, S. Fienberg, and P. Ravikumar
A Hierarchical Graphical Model for Record Linkage 2004
P. Ravikumar and W. W. Cohen
A Secure Protocol for Computing String Distance Metrics 2004
P. Ravikumar, W. W. Cohen, and S. E. Fienberg
Variational Chernoff bounds for graphical models 2004
P. Ravikumar and J. Lafferty
A Comparison of String Distance Metrics for Name-Matching Tasks 2003
W. W. Cohen, P. Ravikumar, and S. Fienberg
A Comparison of String Metrics for Matching Names and Records 2003
W. W. Cohen, P. Ravikumar, and S. Fienberg
Adaptive Name-Matching in Information Integration 2003
Mikhail Bilenko, William W. Cohen, Stephen Fienberg, Raymond J. Mooney, and Pradeep Ravikumar
Labs
Statistical Learning