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A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust
  Low-Rank Matrix Recovery
v1v2 (latest)

A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust Low-Rank Matrix Recovery

28 March 2016
Jianqing Fan
Weichen Wang
Ziwei Zhu
ArXiv (abs)PDFHTML

Papers citing "A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust Low-Rank Matrix Recovery"

34 / 34 papers shown
Title
ISLET: Fast and Optimal Low-rank Tensor Regression via Importance
  Sketching
ISLET: Fast and Optimal Low-rank Tensor Regression via Importance Sketching
Anru R. Zhang
Yuetian Luo
Garvesh Raskutti
M. Yuan
186
44
0
09 Nov 2019
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex
  Relaxation via Nonconvex Optimization
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
Yuling Yan
56
128
0
20 Feb 2019
Adaptive Huber Regression
Adaptive Huber Regression
Qiang Sun
Wen-Xin Zhou
Jianqing Fan
162
281
0
21 Jun 2017
Max-Norm Optimization for Robust Matrix Recovery
Max-Norm Optimization for Robust Matrix Recovery
Ethan X. Fang
Han Liu
Kim-Chuan Toh
Wen-Xin Zhou
45
34
0
24 Sep 2016
On the prediction loss of the lasso in the partially labeled setting
On the prediction loss of the lasso in the partially labeled setting
Pierre C. Bellec
A. Dalalyan
Edwin Grappin
Q. Paris
58
31
0
20 Jun 2016
Sub-Gaussian estimators of the mean of a random matrix with heavy-tailed
  entries
Sub-Gaussian estimators of the mean of a random matrix with heavy-tailed entries
Stanislav Minsker
75
103
0
23 May 2016
Robust Estimators in High Dimensions without the Computational
  Intractability
Robust Estimators in High Dimensions without the Computational Intractability
Ilias Diakonikolas
Gautam Kamath
D. Kane
Jingkai Li
Ankur Moitra
Alistair Stewart
73
513
0
21 Apr 2016
An Introduction to Matrix Concentration Inequalities
An Introduction to Matrix Concentration Inequalities
J. Tropp
170
1,155
0
07 Jan 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
103
195
0
01 Jan 2015
Robust Estimation of High-Dimensional Mean Regression
Robust Estimation of High-Dimensional Mean Regression
Jianqing Fan
Quefeng Li
Yuyan Wang
87
30
0
08 Oct 2014
The lower tail of random quadratic forms, with applications to ordinary
  least squares and restricted eigenvalue properties
The lower tail of random quadratic forms, with applications to ordinary least squares and restricted eigenvalue properties
R. Oliveira
85
101
0
10 Dec 2013
ROP: Matrix recovery via rank-one projections
ROP: Matrix recovery via rank-one projections
T. Tony Cai
Anru R. Zhang
82
149
0
22 Oct 2013
Online and stochastic Douglas-Rachford splitting method for large scale
  machine learning
Online and stochastic Douglas-Rachford splitting method for large scale machine learning
Ziqiang Shi
Rujie Liu
43
4
0
22 Aug 2013
Geometric median and robust estimation in Banach spaces
Geometric median and robust estimation in Banach spaces
Stanislav Minsker
170
311
0
06 Aug 2013
Loss minimization and parameter estimation with heavy tails
Loss minimization and parameter estimation with heavy tails
Daniel J. Hsu
Sivan Sabato
156
188
0
07 Jul 2013
Sparse Representation of a Polytope and Recovery of Sparse Signals and
  Low-rank Matrices
Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-rank Matrices
Tommaso Cai
Anru R. Zhang
88
302
0
05 Jun 2013
Optimal rates of convergence for sparse covariance matrix estimation
Optimal rates of convergence for sparse covariance matrix estimation
T. Cai
Harrison H. Zhou
151
246
0
13 Feb 2013
Adaptive robust variable selection
Adaptive robust variable selection
Jianqing Fan
Yingying Fan
Emre Barut
597
200
0
22 May 2012
Large Covariance Estimation by Thresholding Principal Orthogonal
  Complements
Large Covariance Estimation by Thresholding Principal Orthogonal Complements
Jianqing Fan
Yuan Liao
Martina Mincheva
139
855
0
30 Dec 2011
Accurate Prediction of Phase Transitions in Compressed Sensing via a
  Connection to Minimax Denoising
Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising
D. Donoho
Iain M. Johnstone
Andrea Montanari
127
180
0
04 Nov 2011
Nuclear norm penalization and optimal rates for noisy low rank matrix
  completion
Nuclear norm penalization and optimal rates for noisy low rank matrix completion
V. Koltchinskii
Alexandre B. Tsybakov
Karim Lounici
228
664
0
29 Nov 2010
A Unified Framework for High-Dimensional Analysis of M-Estimators with
  Decomposable Regularizers
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers
S. Negahban
Pradeep Ravikumar
Martin J. Wainwright
Bin Yu
477
1,379
0
13 Oct 2010
Restricted strong convexity and weighted matrix completion: Optimal
  bounds with noise
Restricted strong convexity and weighted matrix completion: Optimal bounds with noise
S. Negahban
Martin J. Wainwright
202
522
0
10 Sep 2010
Challenging the empirical mean and empirical variance: a deviation study
Challenging the empirical mean and empirical variance: a deviation study
O. Catoni
175
466
0
10 Sep 2010
Nearly unbiased variable selection under minimax concave penalty
Nearly unbiased variable selection under minimax concave penalty
Cun-Hui Zhang
342
3,568
0
25 Feb 2010
Estimation of high-dimensional low-rank matrices
Estimation of high-dimensional low-rank matrices
Angelika Rohde
Alexandre B. Tsybakov
270
382
0
29 Dec 2009
Estimation of (near) low-rank matrices with noise and high-dimensional
  scaling
Estimation of (near) low-rank matrices with noise and high-dimensional scaling
S. Negahban
Martin J. Wainwright
236
571
0
27 Dec 2009
Minimax rates of estimation for high-dimensional linear regression over
  $\ell_q$-balls
Minimax rates of estimation for high-dimensional linear regression over ℓq\ell_qℓq​-balls
Garvesh Raskutti
Martin J. Wainwright
Bin Yu
220
575
0
11 Oct 2009
Tree-guided group lasso for multi-response regression with structured
  sparsity, with an application to eQTL mapping
Tree-guided group lasso for multi-response regression with structured sparsity, with an application to eQTL mapping
Seyoung Kim
Eric Xing
122
478
0
08 Sep 2009
Covariance regularization by thresholding
Covariance regularization by thresholding
Peter J. Bickel
Elizaveta Levina
204
1,275
0
20 Jan 2009
Rejoinder: One-step sparse estimates in nonconcave penalized likelihood
  models
Rejoinder: One-step sparse estimates in nonconcave penalized likelihood models
H. Zou
Runze Li
303
1,234
0
07 Aug 2008
Simultaneous analysis of Lasso and Dantzig selector
Simultaneous analysis of Lasso and Dantzig selector
Peter J. Bickel
Yaácov Ritov
Alexandre B. Tsybakov
542
2,531
0
07 Jan 2008
Sparsistency and rates of convergence in large covariance matrix
  estimation
Sparsistency and rates of convergence in large covariance matrix estimation
Clifford Lam
Jianqing Fan
235
610
0
26 Nov 2007
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear
  Norm Minimization
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
Benjamin Recht
Maryam Fazel
P. Parrilo
421
3,772
0
28 Jun 2007
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