Pradeep Ravikumar
Pradeep Ravikumar
Associate Professor, School of Computer Science, Carnegie Mellon University
Verified email at - Homepage
Cited by
Cited by
A Comparison of String Distance Metrics for Name-Matching Tasks.
WW Cohen, P Ravikumar, SE Fienberg
IIWeb 2003, 73-78, 2003
A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers
S Negahban, P Ravikumar, MJ Wainwright, B Yu
Statistical Science 27 (4), 538-557, 2012
High-dimensional Ising model selection using ℓ1-regularized logistic regression
P Ravikumar, MJ Wainwright, JD Lafferty
The Annals of Statistics 38 (3), 1287-1319, 2010
High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence
P Ravikumar, MJ Wainwright, G Raskutti, B Yu
Electronic Journal of Statistics 5, 935-980, 2011
A comparison of string metrics for matching names and records
W Cohen, P Ravikumar, S Fienberg
Workshop on Data Cleaning, Record Linkage, and Object Consolidation at Int …, 2003
Adaptive name matching in information integration
M Bilenko, R Mooney, W Cohen, P Ravikumar, S Fienberg
Intelligent Systems, IEEE 18 (5), 16-23, 2003
Learning with noisy labels
N Natarajan, I Dhillon, P Ravikumar, A Tewari
Advances in Neural Information Processing Systems (NIPS) 26, 1196-1204, 2013
Sparse additive models
P Ravikumar, J Lafferty, H Liu, L Wasserman
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2009
A dirty model for multi-task learning
A Jalali, P Ravikumar, S Sanghavi, C Ruan
Advances in Neural Information Processing Systems (NIPS) 23, 964-972, 2010
Sparse inverse covariance matrix estimation using quadratic approximation
CJ Hsieh, IS Dhillon, P Ravikumar, MA Sustik
Advances in Neural Information Processing Systems (NIPS) 24, 2330-2338, 2011
Information-theoretic lower bounds on the oracle complexity of convex optimization
A Agarwal, MJ Wainwright, PL Bartlett, P Ravikumar
IEEE Transactions on Information Theory 58 (5), 3235-3249, 2012
High-Dimensional Graphical Model Selection Using -Regularized Logistic Regression
MJ Wainwright, JD Lafferty, PK Ravikumar
Advances in neural information processing systems, 1465-1472, 2007
BIG & QUIC: Sparse inverse covariance estimation for a million variables
CJ Hsieh, MA Sustik, I Dhillon, P Ravikumar, R Poldrack
Advances in Neural Information Processing Systems (NIPS) 26, 3165-3173, 2013
Collaborative filtering with graph information: Consistency and scalable methods
N Rao, HF Yu, PK Ravikumar, IS Dhillon
Advances in neural information processing systems, 2107-2115, 2015
QUIC: quadratic approximation for sparse inverse covariance estimation
CJ Hsieh, MA Sustik, IS Dhillon, P Ravikumar
The Journal of Machine Learning Research 15 (1), 2911-2947, 2014
Graphical models via generalized linear models
E Yang, P Ravikumar, GI Allen, Z Liu
Advances in Neural Information Processing Systems (NIPS) 25, 1358-1366, 2012
A hierarchical graphical model for record linkage
P Ravikumar, WW Cohen
Uncertainty in Artificial Intelligence (UAI) 20, 454-461, 2004
Quadratic programming relaxations for metric labeling and markov random field map estimation
P Ravikumar, J Lafferty
International Conference on Machine Learning (ICML) 23, 737-744, 2006
Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of\ boldmath -regularized MLE
G Raskutti, B Yu, MJ Wainwright, PK Ravikumar
Advances in Neural Information Processing Systems (NIPS) 21, 1329-1336, 2008
Pd-sparse: A primal and dual sparse approach to extreme multiclass and multilabel classification
IEH Yen, X Huang, P Ravikumar, K Zhong, I Dhillon
International Conference on Machine Learning, 3069-3077, 2016
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