Pradeep Ravikumar, Ph.D.
Affiliations: | 2007 | Carnegie Mellon University, Pittsburgh, PA |
Area:
statistical machine learningGoogle:
"Pradeep Ravikumar"Mean distance: 18.45 (cluster 29)
Parents
Sign in to add mentorJohn Lafferty | grad student | 2007 | Carnegie Mellon | |
(Approximate inference, structure learning and feature estimation in Markov random fields.) |
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Publications
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Prasad A, Suggala AS, Balakrishnan S, et al. (2020) Robust estimation via robust gradient estimation Journal of the Royal Statistical Society Series B-Statistical Methodology. 82: 601-627 |
Inouye D, Yang E, Allen G, et al. (2017) A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution. Wiley Interdisciplinary Reviews. Computational Statistics. 9 |
Li T, Prasad A, Ravikumar P. (2015) Fast classification rates for high-dimensional Gaussian generative models Advances in Neural Information Processing Systems. 2015: 1054-1062 |
Yang E, Lozano AC, Ravikumar P. (2015) Closed-form estimators for high-dimensional generalized linear models Advances in Neural Information Processing Systems. 2015: 586-594 |
Yang E, Lozano AC, Ravikumar P. (2014) Elementary estimators for high-dimensional linear regression 31st International Conference On Machine Learning, Icml 2014. 2: 1711-1722 |
Yang E, Lozano AC, Ravikumar P. (2014) Elementary estimators for sparse covariance matrices and other structured moments 31st International Conference On Machine Learning, Icml 2014. 2: 1723-1735 |
Jalali A, Ravikumar P, Sanghavi S. (2013) A dirty model for multiple sparse regression Ieee Transactions On Information Theory. 59: 7947-7968 |
Yang E, Tewari A, Ravikumar P. (2013) On robust estimation of high dimensional generalized linear models Ijcai International Joint Conference On Artificial Intelligence. 1834-1840 |
Negahban SN, Ravikumar P, Wainwright MJ, et al. (2012) A unified framework for high-dimensional analysis of m-estimators with decomposable regularizers Statistical Science. 27: 538-557 |
Agarwal A, Bartlett PL, Ravikumar P, et al. (2012) Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization Ieee Transactions On Information Theory. 58: 3235-3249 |