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Accuracy Assessment for High-dimensional Linear Regression
v1v2 (latest)

Accuracy Assessment for High-dimensional Linear Regression

10 March 2016
T. Tony Cai
Zijian Guo
ArXiv (abs)PDFHTML

Papers citing "Accuracy Assessment for High-dimensional Linear Regression"

25 / 25 papers shown
Profiled Transfer Learning for High Dimensional Linear Model
Profiled Transfer Learning for High Dimensional Linear Model
Ziqian Lin
Junlong Zhao
Fang Wang
Han Wang
411
6
0
02 Jun 2024
Root-n consistent semiparametric learning with high-dimensional nuisance
  functions under minimal sparsity
Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity
Lin Liu
Yuhao Wang
327
1
0
07 May 2023
Statistical Inference and Large-scale Multiple Testing for
  High-dimensional Regression Models
Statistical Inference and Large-scale Multiple Testing for High-dimensional Regression ModelsTest (Madrid) (TM), 2023
T. Tony Cai
Zijian Guo
Yin Xia
297
9
0
25 Jan 2023
Finite- and Large- Sample Inference for Model and Coefficients in
  High-dimensional Linear Regression with Repro Samples
Finite- and Large- Sample Inference for Model and Coefficients in High-dimensional Linear Regression with Repro Samples
P. Wang
Min-ge Xie
Linjun Zhang
495
7
0
19 Sep 2022
On Adaptive Confidence Sets for the Wasserstein Distances
On Adaptive Confidence Sets for the Wasserstein Distances
N. Deo
Thibault Randrianarisoa
295
2
0
16 Nov 2021
Comments on Leo Breiman's paper 'Statistical Modeling: The Two Cultures'
  (Statistical Science, 2001, 16(3), 199-231)
Comments on Leo Breiman's paper 'Statistical Modeling: The Two Cultures' (Statistical Science, 2001, 16(3), 199-231)
Jelena Bradic
Yinchu Zhu
123
0
0
21 Mar 2021
Relaxing the Gaussian assumption in Shrinkage and SURE in high dimension
Relaxing the Gaussian assumption in Shrinkage and SURE in high dimensionAnnals of Statistics (Ann. Stat.), 2020
M. Fathi
L. Goldstein
Gesine Reinert
Adrien Saumard
333
12
0
03 Apr 2020
Subsampling Winner Algorithm for Feature Selection in Large Regression
  Data
Subsampling Winner Algorithm for Feature Selection in Large Regression Data
Yiying Fan
Jiayang Sun
135
1
0
07 Feb 2020
Optimal Statistical Inference for Individualized Treatment Effects in
  High-dimensional Models
Optimal Statistical Inference for Individualized Treatment Effects in High-dimensional Models
Tianxi Cai
Tony Cai
Zijian Guo
CMLLM&MA
226
13
0
29 Apr 2019
Optimal Sparsity Testing in Linear regression Model
Optimal Sparsity Testing in Linear regression Model
Alexandra Carpentier
Nicolas Verzélen
234
10
0
25 Jan 2019
The distribution of the Lasso: Uniform control over sparse balls and
  adaptive parameter tuning
The distribution of the Lasso: Uniform control over sparse balls and adaptive parameter tuning
Léo Miolane
Andrea Montanari
328
99
0
03 Nov 2018
Moderate-Dimensional Inferences on Quadratic Functionals in Ordinary
  Least Squares
Moderate-Dimensional Inferences on Quadratic Functionals in Ordinary Least Squares
Xiao Guo
Guang Cheng
188
8
0
02 Oct 2018
Semi-supervised Inference for Explained Variance in High-dimensional
  Linear Regression and Its Applications
Semi-supervised Inference for Explained Variance in High-dimensional Linear Regression and Its Applications
T. Tony Cai
Zijian Guo
281
76
0
16 Jun 2018
High-Dimensional Econometrics and Regularized GMM
High-Dimensional Econometrics and Regularized GMM
A. Belloni
Victor Chernozhukov
Denis Chetverikov
Christian B. Hansen
Kengo Kato
409
69
0
05 Jun 2018
Testability of high-dimensional linear models with non-sparse structures
Testability of high-dimensional linear models with non-sparse structuresAnnals of Statistics (Ann. Stat.), 2018
Jelena Bradic
Jianqing Fan
Yinchu Zhu
461
19
0
26 Feb 2018
Sparse High-Dimensional Linear Regression. Algorithmic Barriers and a
  Local Search Algorithm
Sparse High-Dimensional Linear Regression. Algorithmic Barriers and a Local Search Algorithm
D. Gamarnik
Ilias Zadik
266
22
0
14 Nov 2017
Breaking the curse of dimensionality in regression
Breaking the curse of dimensionality in regression
Yinchu Zhu
Jelena Bradic
361
19
0
01 Aug 2017
Targeted Undersmoothing
Targeted Undersmoothing
Christian B. Hansen
Damian Kozbur
S. Misra
284
12
0
22 Jun 2017
Comments on `High-dimensional simultaneous inference with the bootstrap'
Comments on `High-dimensional simultaneous inference with the bootstrap'
R. Lockhart
R. Samworth
SyDa
159
3
0
29 Mar 2017
Adaptive estimation of the sparsity in the Gaussian vector model
Adaptive estimation of the sparsity in the Gaussian vector model
Alexandra Carpentier
Nicolas Verzélen
245
31
0
01 Mar 2017
High-Dimensional Regression with Binary Coefficients. Estimating Squared
  Error and a Phase Transition
High-Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase TransitionAnnual Conference Computational Learning Theory (COLT), 2017
D. Gamarnik
Ilias Zadik
415
60
0
16 Jan 2017
Linear Hypothesis Testing in Dense High-Dimensional Linear Models
Linear Hypothesis Testing in Dense High-Dimensional Linear ModelsJournal of the American Statistical Association (JASA), 2016
Yinchu Zhu
Jelena Bradic
442
88
0
10 Oct 2016
Adaptive confidence sets for matrix completion
Adaptive confidence sets for matrix completion
Alexandra Carpentier
Olga Klopp
Matthias Loffler
Richard Nickl
244
28
0
17 Aug 2016
Confidence Intervals for Causal Effects with Invalid Instruments using
  Two-Stage Hard Thresholding with Voting
Confidence Intervals for Causal Effects with Invalid Instruments using Two-Stage Hard Thresholding with Voting
Zijian Guo
Hyunseung Kang
T. Tony Cai
Dylan S. Small
338
125
0
16 Mar 2016
De-biasing the Lasso: Optimal Sample Size for Gaussian Designs
De-biasing the Lasso: Optimal Sample Size for Gaussian DesignsAnnals of Statistics (Ann. Stat.), 2015
Adel Javanmard
Andrea Montanari
505
203
0
11 Aug 2015
1
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