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Pradeep Ravikumar

High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence
2011 · Pradeep Ravikumar, Martin J. Wainwright, et al. · Electronic Journal of Statistics · 765
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Sparse Additive Models
2009 · Pradeep Ravikumar, John Lafferty, et al. · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 548
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A review of multivariate distributions for count data derived from the Poisson distribution
2017 · David I. Inouye, Eunho Yang, et al. · Wiley Interdisciplinary Reviews Computational Statistics · 142
On Graphical Models via Univariate Exponential Family Distributions
2013 · Yang, Eunho, Ravikumar, Pradeep, et al. · arXiv (Cornell University) · 68
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On Learning Discrete Graphical Models using Group-Sparse Regularization
2011 · Ali Jalali, Pradeep Ravikumar, et al. · 68
High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression
2008 · Ravikumar, Pradeep, Wainwright, Martin J., et al. · arXiv (Cornell University) · 67
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On NDCG Consistency of Listwise Ranking Methods
2011 · Pradeep Ravikumar, Ambuj Tewari, et al. · 66
LLM-Select: Feature Selection with Large Language Models
2024 · Jeong, Daniel P., Lipton, Zachary C., et al. · arXiv (Cornell University) · 57
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High-Dimensional Graphical Model Selection Using l1 -Regularized Logistic Regression
2007 · Martin J. Wainwright, Pradeep Ravikumar, et al. · The MIT Press eBooks · 50
A Dirty Model for Multiple Sparse Regression
2013 · Ali Jalali, Pradeep Ravikumar, et al. · IEEE Transactions on Information Theory · 46
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Exponential Family Matrix Completion under Structural Constraints
2015 · Gunasekar, Suriya, Ravikumar, Pradeep, et al. · arXiv (Cornell University) · 31
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Learning-based analytical cross-platform performance prediction
2015 · Xinnian Zheng, Pradeep Ravikumar, et al. · International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation · 31
On the Information Theoretic Limits of Learning Ising Models
2014 · Shanmugam, Karthikeyan, Tandon, Rashish, et al. · arXiv (Cornell University) · 31
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XMRF: an R package to fit Markov Networks to high-throughput genetics data
2016 · Ying-Wooi Wan, Genevera I. Allen, et al. · BMC Systems Biology · 22
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A General Framework for Mixed Graphical Models
2014 · Yang, Eunho, Ravikumar, Pradeep, et al. · arXiv (Cornell University) · 19
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Elementary Estimators for Sparse Covariance Matrices and other Structured Moments
2014 · Eunho Yang, Aurélie Lozano, et al. · 19
Shape-based image reconstruction using linearized deformations
2016 · Ozan Öktem, Chong Chen, et al. · Inverse Problems · 17
Error-Correcting Tournaments
2009 · Beygelzimer, Alina, Langford, John, et al. · arXiv (Cornell University) · 15
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Deep Density Destructors
2018 · David I. Inouye, Pradeep Ravikumar · International Conference on Machine Learning · 8
On Proximal Policy Optimization's Heavy-tailed Gradients
2021 · Garg, Saurabh, Zhanson, Joshua, et al. · arXiv (Cornell University) · 7
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Human Boosting
2013 · Harsh Pareek, Pradeep Ravikumar · International Conference on Machine Learning · 5
Context-Sensitive Spelling Correction of Clinical Text via Conditional Independence.
2022 · Juyong Kim, Jeremy C Weiss, et al. · PubMed · 4
Improved Clinical Abbreviation Expansion via Non-Sense-Based Approaches
2020 · Juyong Brian Kim, Linyuan Gong, et al. · 4
A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models
2015 · En-Hsu Yen, Xin Lin, et al. · International Conference on Machine Learning · 4
Global Optimality in Bivariate Gradient-based DAG Learning
2023 · Chang Deng, Kevin Bello, et al. · neural information processing systems · 3
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Works count: 39
Citation count: 2,106
H-index: 17
I10-index: 18
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