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Martin J. Wainwright

Martin J. Wainwright

Award Badge
Mathematics
USA
2026

D-Index & Metrics

Computer Science

D-Index
111
Citations
59050
World Ranking
215
National Ranking
120

Mathematics

D-Index
108
Citations
55512
World Ranking
29
National Ranking
21

Research.com Recognitions

  • 2026 - Research.com Mathematics in United States Leader Award
  • 2025 - Research.com Mathematics in United States Leader Award
  • 2014 - COPSS Presidents' Award For fundamental and groundbreaking contributions to high-dimensional statistics, graphical modeling, machine learning, optimization and algorithms covering deep and elegant mathematical analysis as well as new methodology with wide-ranging implications for numerous applications.
  • 2005 - Fellow of Alfred P. Sloan Foundation

Overview

Martin J. Wainwright is affiliated with MIT in the United States. Their research primarily focuses on the fields of Computer Science and Mathematics, with substantial work in Statistics and Probability, Artificial Intelligence, and Management Science and Operations Research. They have also contributed to areas such as Computer Networks and Communications and Numerical Analysis.

The research topics that Martin J. Wainwright has extensively covered include Statistical Methods and Inference, Advanced Bandit Algorithms Research, Reinforcement Learning in Robotics, Machine Learning and Algorithms, Advanced Causal Inference Techniques, Statistical Methods and Bayesian Inference, and Markov Chains and Monte Carlo Methods.

Martin J. Wainwright has published extensively, with frequent appearances in the following venues:

  • arXiv (Cornell University)
  • The Annals of Statistics
  • IEEE Transactions on Information Theory
  • SIAM Journal on Mathematics of Data Science
  • Bernoulli

Recent notable papers include:

  • "FedSplit: An algorithmic framework for fast federated optimization," 2020, arXiv (Cornell University)
  • "A Permutation-Based Model for Crowd Labeling: Optimal Estimation and Robustness," 2020, IEEE Transactions on Information Theory
  • "Singularity, misspecification and the convergence rate of EM," 2020, The Annals of Statistics
  • "Improved bounds for discretization of Langevin diffusions: Near-optimal rates without convexity," 2022, Bernoulli
  • "Instance-Dependent ℓ-Bounds for Policy Evaluation in Tabular Reinforcement Learning," 2020, IEEE Transactions on Information Theory

Frequent collaborators of Martin J. Wainwright include:

  • Wenlong Mou
  • Michael I. Jordan
  • Koulik Khamaru
  • Peter L. Bartlett
  • Ashwin Pananjady

Martin J. Wainwright has received awards such as the COPSS Presidents' Award in 2014 for contributions covering high-dimensional statistics, graphical modeling, machine learning, optimization, and algorithms. They were also named a Fellow of the Alfred P. Sloan Foundation in 2005.

Best Publications

  • Graphical Models, Exponential Families, and Variational Inference

    Martin J. Wainwright;Michael I. Jordan

  • Statistical Learning with Sparsity: The Lasso and Generalizations

    Trevor Hastie;Robert Tibshirani;Martin Wainwright

  • Image denoising using scale mixtures of Gaussians in the wavelet domain

    J. Portilla;V. Strela;M.J. Wainwright;E.P. Simoncelli

  • Network Coding for Distributed Storage Systems

    A G Dimakis;P B Godfrey;Yunnan Wu;M J Wainwright

  • Network Coding for Distributed Storage Systems

    A.G. Dimakis;P.B. Godfrey;M.J. Wainwright;K. Ramchandran

  • Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $ll _{1}$ -Constrained Quadratic Programming (Lasso)

    M.J. Wainwright

  • A Unified Framework for High-Dimensional Analysis of $M$-Estimators with Decomposable Regularizers

    Sahand N. Negahban;Pradeep Ravikumar;Martin J. Wainwright;Bin Yu

  • Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling

    J. C. Duchi;A. Agarwal;M. J. Wainwright

  • High-Dimensional Statistics: A Non-Asymptotic Viewpoint

    Martin J. Wainwright

  • Local privacy and statistical minimax rates

    John C. Duchi;Michael I. Jordan;Martin J. Wainwright

  • High-dimensional Ising model selection using ℓ1-regularized logistic regression

    Pradeep Ravikumar;Martin J. Wainwright;John D. Lafferty

  • High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence

    Pradeep Ravikumar;Martin J. Wainwright;Garvesh Raskutti;Bin Yu

  • Communication-efficient algorithms for statistical optimization

    Yuchen Zhang;John C. Duchi;Martin J. Wainwright

  • MAP estimation via agreement on trees: message-passing and linear programming

    M.J. Wainwright;T.S. Jaakkola;A.S. Willsky

  • Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization

    XuanLong Nguyen;Martin J Wainwright;M I Jordan

  • High-dimensional Ising model selection using ${ll_1}$-regularized logistic regression

    Pradeep Ravikumar;Martin J. Wainwright;John D. Lafferty

  • Estimation of (near) low-rank matrices with noise and high-dimensional scaling

    Sahand Negahban;Martin J. Wainwright

  • Scale Mixtures of Gaussians and the Statistics of Natural Images

    Martin J Wainwright;Eero P. Simoncelli

  • Using linear programming to Decode Binary linear codes

    J. Feldman;M.J. Wainwright;D.R. Karger

  • A new class of upper bounds on the log partition function

    M.J. Wainwright;T.S. Jaakkola;A.S. Willsky

  • Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions

    Alekh Agarwal;Sahand N. Negahban;Martin J. Wainwright

  • Network Coding for Distributed Storage Systems

    Alexandros G. Dimakis;P. Brighten Godfrey;Martin J. Wainwright;Kannan Ramchandran

Frequent Co-Authors

Michael I. Jordan
Michael I. Jordan University of California, Berkeley
Bin Yu
Bin Yu University of California, Berkeley
John C. Duchi
John C. Duchi Stanford University
Steffen L. Lauritzen
Steffen L. Lauritzen University of Copenhagen
Alekh Agarwal
Alekh Agarwal Google (United States)
Mathias Drton
Mathias Drton Technical University of Munich
Nihar B. Shah
Nihar B. Shah Carnegie Mellon University
Peter L. Bartlett
Peter L. Bartlett University of California, Berkeley
Kannan Ramchandran
Kannan Ramchandran University of California, Berkeley

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