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Improved Matrix Uncertainty Selector

Improved Matrix Uncertainty Selector

19 December 2011
M. Rosenbaum
Alexandre B. Tsybakov
ArXiv (abs)PDFHTML

Papers citing "Improved Matrix Uncertainty Selector"

30 / 30 papers shown
Online Linear Regression with Paid Stochastic Features
Online Linear Regression with Paid Stochastic Features
Nadav Merlis
Kyoungseok Jang
Nicolò Cesa-Bianchi
137
0
0
11 Nov 2025
Imaging Signal Recovery Using Neural Network Priors Under Uncertain
  Forward Model Parameters
Imaging Signal Recovery Using Neural Network Priors Under Uncertain Forward Model Parameters
Xiwen Chen
Wenhui Zhu
Peijie Qiu
Abolfazl Razi
219
0
0
05 May 2024
Low-rank matrix estimation via nonconvex spectral regularized methods in
  errors-in-variables matrix regression
Low-rank matrix estimation via nonconvex spectral regularized methods in errors-in-variables matrix regression
Xin Li
Dongya Wu
215
0
0
05 Mar 2024
High-dimensional Measurement Error Models for Lipschitz Loss
High-dimensional Measurement Error Models for Lipschitz Loss
Xin Ma
Suprateek Kundu
171
2
0
26 Oct 2022
Error-in-variables modelling for operator learning
Error-in-variables modelling for operator learningMathematical and Scientific Machine Learning (MSML), 2022
Ravi G. Patel
Indu Manickam
Myoungkyu Lee
Mamikon A. Gulian
269
4
0
22 Apr 2022
High-dimensional regression with potential prior information on variable
  importance
High-dimensional regression with potential prior information on variable importanceStatistics and computing (Stat Comput), 2021
B. Stokell
Rajen Dinesh Shah
225
0
0
23 Sep 2021
Least Squares with Error in Variables
Least Squares with Error in Variables
David A. Hirshberg
156
9
0
18 Apr 2021
Low-rank matrix estimation in multi-response regression with measurement
  errors: Statistical and computational guarantees
Low-rank matrix estimation in multi-response regression with measurement errors: Statistical and computational guaranteesJournal of Global Optimization (JGO), 2020
Xin Li
Dongya Wu
366
3
0
10 Dec 2020
On Model Identification and Out-of-Sample Prediction of Principal
  Component Regression: Applications to Synthetic Controls
On Model Identification and Out-of-Sample Prediction of Principal Component Regression: Applications to Synthetic Controls
Anish Agarwal
Devavrat Shah
Dennis Shen
544
2
0
27 Oct 2020
Robust Lasso-Zero for sparse corruption and model selection with missing
  covariates
Robust Lasso-Zero for sparse corruption and model selection with missing covariates
Pascaline Descloux
Claire Boyer
Julie Josse
Aude Sportisse
S. Sardy
220
4
0
12 May 2020
Precision Matrix Estimation with Noisy and Missing Data
Precision Matrix Estimation with Noisy and Missing Data
Roger Fan
B. Jang
Yuekai Sun
Shuheng Zhou
215
10
0
07 Apr 2019
On Robustness of Principal Component Regression
On Robustness of Principal Component RegressionNeural Information Processing Systems (NeurIPS), 2019
Anish Agarwal
Devavrat Shah
Dennis Shen
Dogyoon Song
875
89
0
28 Feb 2019
High-dimensional Log-Error-in-Variable Regression with Applications to
  Microbial Compositional Data Analysis
High-dimensional Log-Error-in-Variable Regression with Applications to Microbial Compositional Data Analysis
Pixu Shi
Yuchen Zhou
Anru R. Zhang
237
19
0
28 Nov 2018
HMLasso: Lasso with High Missing Rate
HMLasso: Lasso with High Missing Rate
Masaaki Takada
Hironori Fujisawa
Takeichiro Nishikawa
321
1
0
01 Nov 2018
Sharp oracle inequalities for stationary points of nonconvex penalized
  M-estimators
Sharp oracle inequalities for stationary points of nonconvex penalized M-estimatorsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2018
A. Elsener
Sara van de Geer
211
12
0
27 Feb 2018
Alternating minimization for dictionary learning: Local Convergence
  Guarantees
Alternating minimization for dictionary learning: Local Convergence Guarantees
Niladri S. Chatterji
Peter L. Bartlett
241
28
0
09 Nov 2017
Confidence Bands for Coefficients in High Dimensional Linear Models with
  Error-in-variables
Confidence Bands for Coefficients in High Dimensional Linear Models with Error-in-variables
A. Belloni
Victor Chernozhukov
A. Kaul
351
19
0
01 Mar 2017
Rate Optimal Estimation and Confidence Intervals for High-dimensional
  Regression with Missing Covariates
Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing CovariatesJournal of Multivariate Analysis (J. Multivar. Anal.), 2017
Yining Wang
Jialei Wang
Sivaraman Balakrishnan
Aarti Singh
241
10
0
09 Feb 2017
Errors-in-variables models with dependent measurements
Errors-in-variables models with dependent measurements
M. Rudelson
Shuheng Zhou
208
17
0
15 Nov 2016
CoCoLasso for High-dimensional Error-in-variables Regression
CoCoLasso for High-dimensional Error-in-variables Regression
A. Datta
H. Zou
357
103
0
24 Oct 2015
On estimation of the diagonal elements of a sparse precision matrix
On estimation of the diagonal elements of a sparse precision matrix
Samuel Balmand
A. Dalalyan
447
10
0
18 Apr 2015
High dimensional errors-in-variables models with dependent measurements
High dimensional errors-in-variables models with dependent measurements
M. Rudelson
Shuheng Zhou
260
7
0
09 Feb 2015
An $\{l_1,l_2,l_{\infty}\}$-Regularization Approach to High-Dimensional
  Errors-in-variables Models
An {l1,l2,l∞}\{l_1,l_2,l_{\infty}\}{l1​,l2​,l∞​}-Regularization Approach to High-Dimensional Errors-in-variables Models
A. Belloni
M. Rosenbaum
Alexandre B. Tsybakov
183
10
0
22 Dec 2014
High-Dimensional Semiparametric Selection Models: Estimation Theory with
  an Application to the Retail Gasoline Market
High-Dimensional Semiparametric Selection Models: Estimation Theory with an Application to the Retail Gasoline Market
Ying Zhu
841
1
0
04 Nov 2014
Linear and Conic Programming Estimators in High-Dimensional
  Errors-in-variables Models
Linear and Conic Programming Estimators in High-Dimensional Errors-in-variables Models
A. Belloni
M. Rosenbaum
Alexandre B. Tsybakov
517
74
0
01 Aug 2014
Sparse Linear Models and Two-Stage Estimation in High-Dimensional
  Settings with Possibly Many Endogenous Regressors
Sparse Linear Models and Two-Stage Estimation in High-Dimensional Settings with Possibly Many Endogenous Regressors
Ying Zhu
209
2
0
17 Sep 2013
Robust High Dimensional Sparse Regression and Matching Pursuit
Robust High Dimensional Sparse Regression and Matching Pursuit
Yudong Chen
Constantine Caramanis
Shie Mannor
327
21
0
12 Jan 2013
Robust subspace clustering
Robust subspace clustering
Mahdi Soltanolkotabi
Ehsan Elhamifar
Emmanuel J. Candès
476
372
0
11 Jan 2013
Orthogonal Matching Pursuit with Noisy and Missing Data: Low and High
  Dimensional Results
Orthogonal Matching Pursuit with Noisy and Missing Data: Low and High Dimensional Results
Yudong Chen
Constantine Caramanis
330
18
0
05 Jun 2012
High-dimensional regression with noisy and missing data: Provable
  guarantees with nonconvexity
High-dimensional regression with noisy and missing data: Provable guarantees with nonconvexityNeural Information Processing Systems (NeurIPS), 2011
Po-Ling Loh
Martin J. Wainwright
585
577
0
16 Sep 2011
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