Martin J. Wainwright

45 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0002-8760-2236

Laboratory for Information and Decision Systems, Statistics and Data Science Center, Departments of Electrical Engineering and Computer Science and Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139

Publications

• Near-optimal inference in adaptive linear regression — The Annals of Statistics 2025
• Semiparametric inference based on adaptively collected data — The Annals of Statistics 2025
• Noisy recovery from random linear observations: Sharp minimax rates under elliptical constraints — The Annals of Statistics 2024
• Optimal policy evaluation using kernel-based temporal difference methods — The Annals of Statistics 2024
• Optimally tackling covariate shift in RKHS-based nonparametric regression — The Annals of Statistics 2023
• Towards optimal estimation of bivariate isotonic matrices with unknown permutations — The Annals of Statistics 2020
• Worst-case versus average-case design for estimation from partial pairwise comparisons — The Annals of Statistics 2020
• Singularity, misspecification and the convergence rate of EM — The Annals of Statistics 2020
• Active ranking from pairwise comparisons and when parametric assumptions do not help — The Annals of Statistics 2019
• A unified treatment of multiple testing with prior knowledge using the p-filter — The Annals of Statistics 2019
• A sequential algorithm for false discovery rate control on directed acyclic graphs — Biometrika 2019
• The geometry of hypothesis testing over convex cones: Generalized likelihood ratio tests and minimax radii — The Annals of Statistics 2019
• Minimax Optimal Procedures for Locally Private Estimation — Journal of the American Statistical Association 2018
• Rejoinder — Journal of the American Statistical Association 2018
• Statistical guarantees for the EM algorithm: From population to sample-based analysis — The Annals of Statistics 2017
• Randomized sketches for kernels: Fast and optimal nonparametric regression — The Annals of Statistics 2017
• Statistical and Computational Guarantees for the Baum-Welch Algorithm — Journal of Machine Learning Research 2017
• Support recovery without incoherence: A case for nonconvex regularization — The Annals of Statistics 2017
• A Practical Scheme and Fast Algorithm to Tune the Lasso With Optimality Guarantees — Journal of Machine Learning Research 2016
• Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares — Journal of Machine Learning Research 2016
• Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence — Journal of Machine Learning Research 2016
• On the computational complexity of high-dimensional Bayesian variable selection — The Annals of Statistics 2016
• Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates — Journal of Machine Learning Research 2015
• Regularized M-estimators with Nonconvexity: Statistical and Algorithmic Theory for Local Optima — Journal of Machine Learning Research 2015
• The geometry of kernelized spectral clustering — The Annals of Statistics 2015
• Early Stopping and Non-parametric Regression: An Optimal Data-dependent Stopping Rule — Journal of Machine Learning Research 2014
• Belief Propagation for Continuous State Spaces: Stochastic Message-Passing with Quantitative Guarantees — Journal of Machine Learning Research 2013
• Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses — The Annals of Statistics 2013
• Communication-Efficient Algorithms for Statistical Optimization — Journal of Machine Learning Research 2013
• Restricted Strong Convexity and Weighted Matrix Completion: Optimal Bounds with Noise — Journal of Machine Learning Research 2012
• Discussion: Latent variable graphical model selection via convex optimization — The Annals of Statistics 2012
• Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions — The Annals of Statistics 2012
• Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming — Journal of Machine Learning Research 2012
• Sampled forms of functional PCA in reproducing kernel Hilbert spaces — The Annals of Statistics 2012
• High-dimensional regression with noisy and missing data: Provable guarantees with nonconvexity — The Annals of Statistics 2012
• Fast global convergence of gradient methods for high-dimensional statistical recovery — The Annals of Statistics 2012
• Estimation of (near) low-rank matrices with noise and high-dimensional scaling — The Annals of Statistics 2011
• Support union recovery in high-dimensional multivariate regression — The Annals of Statistics 2011
• Restricted Eigenvalue Properties for Correlated Gaussian Designs — Journal of Machine Learning Research 2010
• High-dimensional Ising model selection using ℓ1-regularized logistic regression — The Annals of Statistics 2010
• High-dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency — Journal of Machine Learning Research 2010
• Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes — Journal of Machine Learning Research 2010
• On surrogate loss functions and f-divergences — The Annals of Statistics 2009
• Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting — Journal of Machine Learning Research 2006
• Doubly High-Dimensional Contextual Bandits: An Interpretable Model for Joint Assortment-Pricing — Management Science