Martin Wainwright

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Bin YUProfessor of Statistics and EECS, UC BerkeleyVerified email at stat.berkeley.edu
John DuchiAssociate Professor of Statistics and Electrical Engineering, Stanford UniversityVerified email at stanford.edu
Alan S. WillskyProfessor of EECS, MITVerified email at mit.edu
Sahand NegahbanAssociate Professor, Yale UniversityVerified email at yale.edu
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Kannan RamchandranProfessor of Electrical Engineering and Computer Science, UC BerkeleyVerified email at eecs.berkeley.edu
Alekh AgarwalGoogleVerified email at google.com
Eero P SimoncelliSilver Professor of Neural Science, Mathematics, Data Science, and Psychology, NYU.Verified email at nyu.edu
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Alexandros G DimakisProfessor, ECE University of Texas at AustinVerified email at austin.utexas.edu
XuanLong NguyenUniversity of MichiganVerified email at umich.edu
Yuchen ZhangResearch Scientist at ByteDanceVerified email at microsoft.com
Tommi JaakkolaMITVerified email at csail.mit.edu
Sivaraman BalakrishnanCarnegie Mellon UniversityVerified email at stat.cmu.edu
Ashwin PananjadyGeorgia Institute of TechnologyVerified email at gatech.edu
Borivoje NikolicUniversity of California BerkeleyVerified email at berkeley.edu
Nihar B. ShahML and CS departments, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Koulik KhamaruAssistant Professor, Department Of Statistics, Rutgers.Verified email at berkeley.edu
Lara DolecekElectrical Engineering, UCLAVerified email at ee.ucla.edu

Martin Wainwright

Professor, EECS/Mathematics, Massachusetts Institute of Technology

Verified email at mit.edu - Homepage

Statistics machine learning optimization information theory artificial intelligence


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Graphical models, exponential families, and variational inference MJ Wainwright, MI Jordan Foundations and Trends® in Machine Learning 1 (1–2), 1-305, 2008	5246	2008
Statistical learning with sparsity: the lasso and generalizations T Hastie, R Tibshirani, M Wainwright CRC press, 2015	3645	2015
Image denoising using scale mixtures of Gaussians in the wavelet domain J Portilla, V Strela, MJ Wainwright, EP Simoncelli IEEE Transactions on Image processing 12 (11), 1338-1351, 2003	3118	2003
Network coding for distributed storage systems AG Dimakis, PB Godfrey, Y Wu, MJ Wainwright, K Ramchandran IEEE transactions on information theory 56 (9), 4539-4551, 2010	2478	2010
High-dimensional statistics: A non-asymptotic viewpoint MJ Wainwright Cambridge university press, 2019	2285	2019
Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using -Constrained Quadratic Programming (Lasso) MJ Wainwright IEEE transactions on information theory 55 (5), 2183-2202, 2009	1516	2009
Dual averaging for distributed optimization: Convergence analysis and network scaling JC Duchi, A Agarwal, MJ Wainwright IEEE Transactions on Automatic control 57 (3), 592-606, 2011	1315	2011
A Unified Framework for High-Dimensional Analysis of -Estimators with Decomposable Regularizers SN Negahban, P Ravikumar, MJ Wainwright, B Yu	1159	2012
High-dimensional Ising model selection using ℓ₁-regularized logistic regression P Ravikumar, MJ Wainwright, JD Lafferty	1140	2010
Local privacy and statistical minimax rates JC Duchi, MI Jordan, MJ Wainwright 2013 IEEE 54th Annual Symposium on Foundations of Computer Science, 429-438, 2013	1133	2013
High-dimensional covariance estimation by minimizing ℓ₁-penalized log-determinant divergence P Ravikumar, MJ Wainwright, G Raskutti, B Yu	1001	2011
MAP estimation via agreement on trees: message-passing and linear programming MJ Wainwright, TS Jaakkola, AS Willsky IEEE transactions on information theory 51 (11), 3697-3717, 2005	802	2005
Estimating divergence functionals and the likelihood ratio by convex risk minimization XL Nguyen, MJ Wainwright, MI Jordan IEEE Transactions on Information Theory 56 (11), 5847-5861, 2010	769	2010
Scale mixtures of Gaussians and the statistics of natural images MJ Wainwright, E Simoncelli Advances in neural information processing systems 12, 1999	661	1999
Estimation of (near) low-rank matrices with noise and high-dimensional scaling S Negahban, MJ Wainwright	630	2011
Minimax Rates of Estimation for High-Dimensional Linear Regression Over -Balls G Raskutti, MJ Wainwright, B Yu IEEE transactions on information theory 57 (10), 6976-6994, 2011	628	2011
High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity PL Loh, MJ Wainwright Advances in neural information processing systems 24, 2011	619	2011
Using linear programming to decode binary linear codes J Feldman, MJ Wainwright, DR Karger IEEE Transactions on Information Theory 51 (3), 954-972, 2005	579	2005
Hopskipjumpattack: A query-efficient decision-based attack J Chen, MI Jordan, MJ Wainwright 2020 ieee symposium on security and privacy (sp), 1277-1294, 2020	568	2020
Restricted eigenvalue properties for correlated Gaussian designs G Raskutti, MJ Wainwright, B Yu The Journal of Machine Learning Research 11, 2241-2259, 2010	567	2010

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