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Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using l1-Constrained Quadratic Programming (Lasso)

IEEE transactions on information theory, 2009, Vol.55 (5), p.2183-2202

WAINWRIGHT, Martin J

2009

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STATISTICAL GUARANTEES FOR THE EM ALGORITHM: FROM POPULATION TO SAMPLE-BASED ANALYSIS

The Annals of statistics, 2017-02, Vol.45 (1), p.77-120

2017

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RANDOMIZED SKETCHES FOR KERNELS: FAST AND OPTIMAL NONPARAMETRIC REGRESSION

The Annals of statistics, 2017-06, Vol.45 (3), p.991-1023

2017

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Minimax Optimal Procedures for Locally Private Estimation

Journal of the American Statistical Association, 2018-01, Vol.113 (521), p.182-201

2018

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SUPPORT RECOVERY WITHOUT INCOHERENCE: A CASE FOR NONCONVEX REGULARIZATION

The Annals of statistics, 2017-12, Vol.45 (6), p.2455-2482

2017

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Information-Theoretic Limits on Sparsity Recovery in the High-Dimensional and Noisy Setting

IEEE transactions on information theory, 2009-12, Vol.55 (12), p.5728-5741

Wainwright, M.J.

2009

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ESTIMATION OF (NEAR) LOW-RANK MATRICES WITH NOISE AND HIGH-DIMENSIONAL SCALING

The Annals of statistics, 2011-04, Vol.39 (2), p.1069-1097

2011

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Linear Regression With Shuffled Data: Statistical and Computational Limits of Permutation Recovery

IEEE transactions on information theory, 2018-05, Vol.64 (5), p.3286-3300

2018

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

Statistical science, 2012-11, Vol.27 (4), p.538-557

2012

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NOISY MATRIX DECOMPOSITION VIA CONVEX RELAXATION: OPTIMAL RATES IN HIGH DIMENSIONS

The Annals of statistics, 2012-04, Vol.40 (2), p.1171-1197

2012

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Minimax Rates of Estimation for High-Dimensional Linear Regression Over lq-Balls

IEEE transactions on information theory, 2011-10, Vol.57 (10), p.6976-6994

2011

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Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization

IEEE transactions on information theory, 2010-11, Vol.56 (11), p.5847-5861

2010

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FAST GLOBAL CONVERGENCE OF GRADIENT METHODS FOR HIGH-DIMENSIONAL STATISTICAL RECOVERY

The Annals of statistics, 2012-10, Vol.40 (5), p.2452-2482

2012

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ON THE COMPUTATIONAL COMPLEXITY OF HIGH-DIMENSIONAL BAYESIAN VARIABLE SELECTION

The Annals of statistics, 2016-12, Vol.44 (6), p.2497-2532

2016

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Information-Theoretic Limits of Selecting Binary Graphical Models in High Dimensions

IEEE transactions on information theory, 2012-07, Vol.58 (7), p.4117-4134

2012

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HIGH-DIMENSIONAL ISING MODEL SELECTION USING l1-REGULARIZED LOGISTIC REGRESSION

The Annals of statistics, 2010-06, Vol.38 (3), p.1287-1319

2010

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Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling

IEEE transactions on automatic control, 2012-03, Vol.57 (3), p.592-606

2012

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ACTIVE RANKING FROM PAIRWISE COMPARISONS AND WHEN PARAMETRIC ASSUMPTIONS DO NOT HELP

The Annals of statistics, 2019-12, Vol.47 (6), p.3099-3126

2019

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HIGH-DIMENSIONAL REGRESSION WITH NOISY AND MISSING DATA: PROVABLE GUARANTEES WITH NONCONVEXITY

The Annals of statistics, 2012-06, Vol.40 (3), p.1637-1664

2012

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Network Coding for Distributed Storage Systems

IEEE transactions on information theory, 2010-09, Vol.56 (9), p.4539-4551

2010

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THE GEOMETRY OF KERNELIZED SPECTRAL CLUSTERING

The Annals of statistics, 2015-04, Vol.43 (2), p.819-846

2015

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Optimally tackling covariate shift in RKHS-based nonparametric regression

The Annals of statistics, 2023-04, Vol.51 (2), p.738

2023

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Information-Theoretic Lower Bounds on the Oracle Complexity of Stochastic Convex Optimization

IEEE transactions on information theory, 2012-05, Vol.58 (5), p.3235-3249

2012

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TOWARDS OPTIMAL ESTIMATION OF BIVARIATE ISOTONIC MATRICES WITH UNKNOWN PERMUTATIONS

The Annals of statistics, 2020-12, Vol.48 (6), p.3183-3205

2020

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Randomized Smoothing for Stochastic Optimization

SIAM journal on optimization, 2012-01, Vol.22 (2), p.674-701

2012

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Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using l1-Constrained Quadratic Programming (Lasso)

STATISTICAL GUARANTEES FOR THE EM ALGORITHM: FROM POPULATION TO SAMPLE-BASED ANALYSIS

RANDOMIZED SKETCHES FOR KERNELS: FAST AND OPTIMAL NONPARAMETRIC REGRESSION

Minimax Optimal Procedures for Locally Private Estimation

SUPPORT RECOVERY WITHOUT INCOHERENCE: A CASE FOR NONCONVEX REGULARIZATION

Information-Theoretic Limits on Sparsity Recovery in the High-Dimensional and Noisy Setting

ESTIMATION OF (NEAR) LOW-RANK MATRICES WITH NOISE AND HIGH-DIMENSIONAL SCALING

Linear Regression With Shuffled Data: Statistical and Computational Limits of Permutation Recovery

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

NOISY MATRIX DECOMPOSITION VIA CONVEX RELAXATION: OPTIMAL RATES IN HIGH DIMENSIONS

Minimax Rates of Estimation for High-Dimensional Linear Regression Over lq-Balls

Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization

FAST GLOBAL CONVERGENCE OF GRADIENT METHODS FOR HIGH-DIMENSIONAL STATISTICAL RECOVERY

ON THE COMPUTATIONAL COMPLEXITY OF HIGH-DIMENSIONAL BAYESIAN VARIABLE SELECTION

Information-Theoretic Limits of Selecting Binary Graphical Models in High Dimensions

HIGH-DIMENSIONAL ISING MODEL SELECTION USING l1-REGULARIZED LOGISTIC REGRESSION

Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling

ACTIVE RANKING FROM PAIRWISE COMPARISONS AND WHEN PARAMETRIC ASSUMPTIONS DO NOT HELP

HIGH-DIMENSIONAL REGRESSION WITH NOISY AND MISSING DATA: PROVABLE GUARANTEES WITH NONCONVEXITY

Network Coding for Distributed Storage Systems

THE GEOMETRY OF KERNELIZED SPECTRAL CLUSTERING

Optimally tackling covariate shift in RKHS-based nonparametric regression

Information-Theoretic Lower Bounds on the Oracle Complexity of Stochastic Convex Optimization

TOWARDS OPTIMAL ESTIMATION OF BIVARIATE ISOTONIC MATRICES WITH UNKNOWN PERMUTATIONS

Randomized Smoothing for Stochastic Optimization

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