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High Dimensional Robust M-Estimation: Asymptotic Variance via
  Approximate Message Passing

High Dimensional Robust M-Estimation: Asymptotic Variance via Approximate Message Passing

28 October 2013
D. Donoho
Andrea Montanari
ArXivPDFHTML

Papers citing "High Dimensional Robust M-Estimation: Asymptotic Variance via Approximate Message Passing"

46 / 46 papers shown
Title
Derivatives and residual distribution of regularized M-estimators with application to adaptive tuning
Derivatives and residual distribution of regularized M-estimators with application to adaptive tuning
Pierre C. Bellec
Yi Shen
48
13
0
03 Jan 2025
Analysis of High-dimensional Gaussian Labeled-unlabeled Mixture Model via Message-passing Algorithm
Analysis of High-dimensional Gaussian Labeled-unlabeled Mixture Model via Message-passing Algorithm
Xiaosi Gu
Tomoyuki Obuchi
74
0
0
29 Nov 2024
Understanding Optimal Feature Transfer via a Fine-Grained Bias-Variance Analysis
Understanding Optimal Feature Transfer via a Fine-Grained Bias-Variance Analysis
Yufan Li
Subhabrata Sen
Ben Adlam
MLT
51
1
0
18 Apr 2024
Existence of solutions to the nonlinear equations characterizing the
  precise error of M-estimators
Existence of solutions to the nonlinear equations characterizing the precise error of M-estimators
Pierre C. Bellec
Takuya Koriyama
16
2
0
20 Dec 2023
Random Matrix Analysis to Balance between Supervised and Unsupervised
  Learning under the Low Density Separation Assumption
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
Vasilii Feofanov
Malik Tiomoko
Aladin Virmaux
31
5
0
20 Oct 2023
Moment-Based Adjustments of Statistical Inference in High-Dimensional
  Generalized Linear Models
Moment-Based Adjustments of Statistical Inference in High-Dimensional Generalized Linear Models
Kazuma Sawaya
Yoshimasa Uematsu
Masaaki Imaizumi
34
2
0
28 May 2023
Approximate message passing from random initialization with applications
  to $\mathbb{Z}_{2}$ synchronization
Approximate message passing from random initialization with applications to Z2\mathbb{Z}_{2}Z2​ synchronization
Gen Li
Wei Fan
Yuting Wei
26
10
0
07 Feb 2023
Near-optimal multiple testing in Bayesian linear models with
  finite-sample FDR control
Near-optimal multiple testing in Bayesian linear models with finite-sample FDR control
Taejoon Ahn
Licong Lin
Song Mei
24
3
0
04 Nov 2022
Robust and Tuning-Free Sparse Linear Regression via Square-Root Slope
Robust and Tuning-Free Sparse Linear Regression via Square-Root Slope
Stanislav Minsker
M. Ndaoud
Lan Wang
40
8
0
30 Oct 2022
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized
  Linear Models
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Lijia Zhou
Frederic Koehler
Pragya Sur
Danica J. Sutherland
Nathan Srebro
83
9
0
21 Oct 2022
Adaptive and Robust Multi-Task Learning
Adaptive and Robust Multi-Task Learning
Yaqi Duan
Kaizheng Wang
75
23
0
10 Feb 2022
Noisy linear inverse problems under convex constraints: Exact risk
  asymptotics in high dimensions
Noisy linear inverse problems under convex constraints: Exact risk asymptotics in high dimensions
Q. Han
29
3
0
20 Jan 2022
Approximate Message Passing for orthogonally invariant ensembles:
  Multivariate non-linearities and spectral initialization
Approximate Message Passing for orthogonally invariant ensembles: Multivariate non-linearities and spectral initialization
Xinyi Zhong
Tianhao Wang
Zhou-Yang Fan
29
20
0
05 Oct 2021
Graph-based Approximate Message Passing Iterations
Graph-based Approximate Message Passing Iterations
Cédric Gerbelot
Raphael Berthier
40
46
0
24 Sep 2021
Performance of Bayesian linear regression in a model with mismatch
Performance of Bayesian linear regression in a model with mismatch
Jean Barbier
Wei-Kuo Chen
D. Panchenko
Manuel Sáenz
40
22
0
14 Jul 2021
Whiteout: when do fixed-X knockoffs fail?
Whiteout: when do fixed-X knockoffs fail?
Xiao Li
William Fithian
18
9
0
30 Jun 2021
Activation function design for deep networks: linearity and effective
  initialisation
Activation function design for deep networks: linearity and effective initialisation
Michael Murray
V. Abrol
Jared Tanner
ODL
LLMSV
29
18
0
17 May 2021
Label-Imbalanced and Group-Sensitive Classification under
  Overparameterization
Label-Imbalanced and Group-Sensitive Classification under Overparameterization
Ganesh Ramachandra Kini
Orestis Paraskevas
Samet Oymak
Christos Thrampoulidis
27
93
0
02 Mar 2021
Learning curves of generic features maps for realistic datasets with a
  teacher-student model
Learning curves of generic features maps for realistic datasets with a teacher-student model
Bruno Loureiro
Cédric Gerbelot
Hugo Cui
Sebastian Goldt
Florent Krzakala
M. Mézard
Lenka Zdeborová
35
135
0
16 Feb 2021
Smoothed Quantile Regression with Large-Scale Inference
Smoothed Quantile Regression with Large-Scale Inference
Xuming He
Xiaoou Pan
Kean Ming Tan
Wen-Xin Zhou
22
93
0
09 Dec 2020
Precise Statistical Analysis of Classification Accuracies for
  Adversarial Training
Precise Statistical Analysis of Classification Accuracies for Adversarial Training
Adel Javanmard
Mahdi Soltanolkotabi
AAML
28
62
0
21 Oct 2020
The Lasso with general Gaussian designs with applications to hypothesis
  testing
The Lasso with general Gaussian designs with applications to hypothesis testing
Michael Celentano
Andrea Montanari
Yuting Wei
42
63
0
27 Jul 2020
A Precise High-Dimensional Asymptotic Theory for Boosting and
  Minimum-$\ell_1$-Norm Interpolated Classifiers
A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-ℓ1\ell_1ℓ1​-Norm Interpolated Classifiers
Tengyuan Liang
Pragya Sur
33
68
0
05 Feb 2020
De-biasing convex regularized estimators and interval estimation in
  linear models
De-biasing convex regularized estimators and interval estimation in linear models
Pierre C. Bellec
Cun-Hui Zhang
27
20
0
26 Dec 2019
A Model of Double Descent for High-dimensional Binary Linear
  Classification
A Model of Double Descent for High-dimensional Binary Linear Classification
Zeyu Deng
A. Kammoun
Christos Thrampoulidis
36
145
0
13 Nov 2019
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate
  Message Passing
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing
Zhiqi Bu
Jason M. Klusowski
Cynthia Rush
Weijie Su
36
43
0
17 Jul 2019
Exact high-dimensional asymptotics for Support Vector Machine
Exact high-dimensional asymptotics for Support Vector Machine
Haoyang Liu
33
2
0
13 May 2019
Outlier-robust estimation of a sparse linear model using
  $\ell_1$-penalized Huber's $M$-estimator
Outlier-robust estimation of a sparse linear model using ℓ1\ell_1ℓ1​-penalized Huber's MMM-estimator
A. Dalalyan
Philip Thompson
23
67
0
12 Apr 2019
Fundamental Barriers to High-Dimensional Regression with Convex
  Penalties
Fundamental Barriers to High-Dimensional Regression with Convex Penalties
Michael Celentano
Andrea Montanari
33
46
0
25 Mar 2019
Approximate Survey Propagation for Statistical Inference
Approximate Survey Propagation for Statistical Inference
F. Antenucci
Florent Krzakala
Pierfrancesco Urbani
Lenka Zdeborová
29
21
0
03 Jul 2018
Entropy and mutual information in models of deep neural networks
Entropy and mutual information in models of deep neural networks
Marylou Gabrié
Andre Manoel
Clément Luneau
Jean Barbier
N. Macris
Florent Krzakala
Lenka Zdeborová
30
179
0
24 May 2018
A modern maximum-likelihood theory for high-dimensional logistic
  regression
A modern maximum-likelihood theory for high-dimensional logistic regression
Pragya Sur
Emmanuel J. Candes
23
285
0
19 Mar 2018
Optimal Errors and Phase Transitions in High-Dimensional Generalized
  Linear Models
Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models
Jean Barbier
Florent Krzakala
N. Macris
Léo Miolane
Lenka Zdeborová
28
259
0
10 Aug 2017
Asymptotics For High Dimensional Regression M-Estimates: Fixed Design
  Results
Asymptotics For High Dimensional Regression M-Estimates: Fixed Design Results
Lihua Lei
Peter J. Bickel
N. Karoui
24
39
0
19 Dec 2016
Statistics of Robust Optimization: A Generalized Empirical Likelihood
  Approach
Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach
John C. Duchi
Peter Glynn
Hongseok Namkoong
4
318
0
11 Oct 2016
An equivalence between high dimensional Bayes optimal inference and
  M-estimation
An equivalence between high dimensional Bayes optimal inference and M-estimation
Madhu S. Advani
Surya Ganguli
21
16
0
22 Sep 2016
Can we trust the bootstrap in high-dimension?
Can we trust the bootstrap in high-dimension?
N. Karoui
E. Purdom
35
24
0
02 Aug 2016
Finite Sample Analysis of Approximate Message Passing Algorithms
Finite Sample Analysis of Approximate Message Passing Algorithms
Cynthia Rush
R. Venkataramanan
26
58
0
06 Jun 2016
Overcoming The Limitations of Phase Transition by Higher Order Analysis
  of Regularization Techniques
Overcoming The Limitations of Phase Transition by Higher Order Analysis of Regularization Techniques
Haolei Weng
A. Maleki
Le Zheng
19
31
0
23 Mar 2016
False Discoveries Occur Early on the Lasso Path
False Discoveries Occur Early on the Lasso Path
Weijie Su
M. Bogdan
Emmanuel Candes
35
180
0
05 Nov 2015
Robust Covariance and Scatter Matrix Estimation under Huber's
  Contamination Model
Robust Covariance and Scatter Matrix Estimation under Huber's Contamination Model
Mengjie Chen
Chao Gao
Zhao Ren
25
164
0
01 Jun 2015
Variance Breakdown of Huber (M)-estimators: $n/p \rightarrow m \in
  (1,\infty)$
Variance Breakdown of Huber (M)-estimators: n/p→m∈(1,∞)n/p \rightarrow m \in (1,\infty)n/p→m∈(1,∞)
D. Donoho
Andrea Montanari
29
14
0
06 Mar 2015
Statistical consistency and asymptotic normality for high-dimensional
  robust M-estimators
Statistical consistency and asymptotic normality for high-dimensional robust M-estimators
Po-Ling Loh
37
192
0
01 Jan 2015
Statistical Estimation: From Denoising to Sparse Regression and Hidden
  Cliques
Statistical Estimation: From Denoising to Sparse Regression and Hidden Cliques
Eric W. Tramel
Santhosh Kumar
A. Giurgiu
Andrea Montanari
26
11
0
19 Sep 2014
On the Optimality of Averaging in Distributed Statistical Learning
On the Optimality of Averaging in Distributed Statistical Learning
Jonathan D. Rosenblatt
B. Nadler
FedML
37
109
0
10 Jul 2014
Phase Diagram and Approximate Message Passing for Blind Calibration and
  Dictionary Learning
Phase Diagram and Approximate Message Passing for Blind Calibration and Dictionary Learning
Florent Krzakala
M. Mézard
Lenka Zdeborová
75
37
0
24 Jan 2013
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