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All publications by Martin J. Wainwright
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Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation
John Duchi, Martin J. Wainwright and Michael Jordan
Advances in Neural Information Processing Systems 26, 2013


Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima
Po-ling Loh and Martin J. Wainwright
Advances in Neural Information Processing Systems 26, 2013


Information-theoretic lower bounds for distributed statistical estimation with communication constraints
Yuchen Zhang, John Duchi, Michael Jordan and Martin J. Wainwright
Advances in Neural Information Processing Systems 26, 2013


Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses
Po-ling Loh and Martin J. Wainwright
Advances in Neural Information Processing Systems 25, 2012


Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions
Alekh Agarwal, Sahand Negahban and Martin J. Wainwright
Advances in Neural Information Processing Systems 25, 2012


Communication-Efficient Algorithms for Statistical Optimization
Yuchen Zhang, Martin J. Wainwright and John C. Duchi
Advances in Neural Information Processing Systems 25, 2012


Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods
Andre Wibisono, Martin J. Wainwright, Michael I. Jordan and John C. Duchi
Advances in Neural Information Processing Systems 25, 2012


Privacy Aware Learning
Martin J. Wainwright, Michael I. Jordan and John C. Duchi
Advances in Neural Information Processing Systems 25, 2012


High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity
Po-ling Loh and Martin J. Wainwright
Advances in Neural Information Processing Systems 24, 2011


A More Powerful Two-Sample Test in High Dimensions using Random Projection
Miles Lopes, Laurent Jacob and Martin J. Wainwright
Advances in Neural Information Processing Systems 24, 2011


Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions
Alekh Agarwal, Sahand Negahban and Martin J. Wainwright
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Estimation of (near) low-rank matrices with noise and high-dimensional scaling
Sahand Negahban and Martin J. Wainwright
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Fast global convergence rates of gradient methods for high-dimensional statistical recovery
Alekh Agarwal, Sahand Negahban and Martin J. Wainwright
Advances in Neural Information Processing Systems 23, 2010


Distributed Dual Averaging In Networks
Alekh Agarwal, Martin J. Wainwright and John C. Duchi
Advances in Neural Information Processing Systems 23, 2010


Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness
Garvesh Raskutti, Bin Yu and Martin J. Wainwright
Advances in Neural Information Processing Systems 22, 2009


A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
Sahand Negahban, Bin Yu, Martin J. Wainwright and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 22, 2009


Information-theoretic lower bounds on the oracle complexity of convex optimization
Alekh Agarwal, Martin J. Wainwright, Peter L. Bartlett and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 22, 2009


Message-passing for graph-structured linear programs: proximal projections, convergence and rounding schemes
Pradeep D. Ravikumar, Alekh Agarwal and Martin J. Wainwright
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-regularized MLE
Garvesh Raskutti, Bin Yu, Martin J. Wainwright and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 21, 2008


Phase transitions for high-dimensional joint support recovery
Sahand Negahban and Martin J. Wainwright
Advances in Neural Information Processing Systems 21, 2008


High-dimensional support union recovery in multivariate regression
Guillaume R. Obozinski, Martin J. Wainwright and Michael I. Jordan
Advances in Neural Information Processing Systems 21, 2008


Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization
Xuanlong Nguyen, Martin J. Wainwright and Michael I. Jordan
Advances in Neural Information Processing Systems 20, 2007


Loop Series and Bethe Variational Bounds in Attractive Graphical Models
Alan S. Willsky, Erik B. Sudderth and Martin J. Wainwright
Advances in Neural Information Processing Systems 20, 2007


Estimating the "Wrong" Graphical Model: Benefits in the Computation-Limited Setting
Martin J. Wainwright
Journal of Machine Learning Research, 2006


High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression
Martin J. Wainwright, John D. Lafferty and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 19, 2006


Estimating the wrong Markov random field: Benefits in the computation-limited setting
Martin J. Wainwright
Advances in Neural Information Processing Systems 18, 2005


Decentralized detection and classification using kernel methods
Xuanlong Nguyen, Martin J. Wainwright and Michael I. Jordan
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Semidefinite Relaxations for Approximate Inference on Graphs with Cycles
Michael I. Jordan and Martin J. Wainwright
Advances in Neural Information Processing Systems 16, 2003


Exact MAP Estimates by (Hyper)tree Agreement
Alan S. Willsky, Martin J. Wainwright and Tommi S. Jaakkola
Advances in Neural Information Processing Systems 15, 2002


Tree-based reparameterization for approximate inference on loopy graphs
Martin J. Wainwright, Tommi Jaakkola and Alan S. Willsky
Advances in Neural Information Processing Systems 14, 2001