| A Comparison of String Distance Metrics for Name-Matching Tasks. WW Cohen, P Ravikumar, SE Fienberg IIWeb 3, 73-78, 2003 | 1983 | 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 | 1491 | 2012 |
| Learning with noisy labels N Natarajan, I Dhillon, P Ravikumar, A Tewari Advances in Neural Information Processing Systems (NIPS) 26, 1196-1204, 2013 | 1204 | 2013 |
| 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 | 1159 | 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 | 1004 | 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 | 835 | 2003 |
| Sparse additive models P Ravikumar, J Lafferty, H Liu, L Wasserman Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2009 | 790 | 2009 |
| Adaptive name matching in information integration M Bilenko, R Mooney, W Cohen, P Ravikumar, S Fienberg Intelligent Systems, IEEE 18 (5), 16-23, 2003 | 751 | 2003 |
| Dags with no tears: Continuous optimization for structure learning X Zheng, B Aragam, PK Ravikumar, EP Xing Advances in neural information processing systems 31, 2018 | 665 | 2018 |
| 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 | 475 | 2012 |
| 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 | 473 | 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 | 419 | 2011 |
| On the (in) fidelity and sensitivity of explanations CK Yeh, CY Hsieh, A Suggala, DI Inouye, PK Ravikumar Advances in Neural Information Processing Systems 32, 2019 | 366 | 2019 |
| Collaborative filtering with graph information: Consistency and scalable methods N Rao, HF Yu, PK Ravikumar, IS Dhillon Advances in neural information processing systems 28, 2015 | 316 | 2015 |
| High-Dimensional Graphical Model Selection Using -Regularized Logistic Regression MJ Wainwright, JD Lafferty, PK Ravikumar Advances in neural information processing systems, 1465-1472, 2007 | 259 | 2007 |
| On completeness-aware concept-based explanations in deep neural networks CK Yeh, B Kim, S Arik, CL Li, T Pfister, P Ravikumar Advances in neural information processing systems 33, 20554-20565, 2020 | 240* | 2020 |
| The risks of invariant risk minimization E Rosenfeld, P Ravikumar, A Risteski arXiv preprint arXiv:2010.05761, 2020 | 233 | 2020 |
| Robust estimation via robust gradient estimation A Prasad, AS Suggala, S Balakrishnan, P Ravikumar Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2020 | 227 | 2020 |
| QUIC: quadratic approximation for sparse inverse covariance estimation. CJ Hsieh, MA Sustik, IS Dhillon, P Ravikumar J. Mach. Learn. Res. 15 (1), 2911-2947, 2014 | 225 | 2014 |
| 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 | 222 | 2013 |
