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In Defense of the Indefensible: A Very Naive Approach to
  High-Dimensional Inference
v1v2v3 (latest)

In Defense of the Indefensible: A Very Naive Approach to High-Dimensional Inference

16 May 2017
Sen Zhao
Daniela Witten
Ali Shojaie
ArXiv (abs)PDFHTML

Papers citing "In Defense of the Indefensible: A Very Naive Approach to High-Dimensional Inference"

15 / 15 papers shown
Title
Machine learning the first stage in 2SLS: Practical guidance from bias decomposition and simulation
Machine learning the first stage in 2SLS: Practical guidance from bias decomposition and simulation
Connor Lennon
Edward Rubin
Glen Waddell
53
0
0
19 May 2025
Predictive Performance Test based on the Exhaustive Nested
  Cross-Validation for High-dimensional data
Predictive Performance Test based on the Exhaustive Nested Cross-Validation for High-dimensional data
I. I. Gauran
H. Ombao
Zhaoxia Yu
27
0
0
06 Aug 2024
Adaptive debiased machine learning using data-driven model selection
  techniques
Adaptive debiased machine learning using data-driven model selection techniques
L. Laan
M. Carone
Alexander Luedtke
Mark van der Laan
74
9
0
24 Jul 2023
Semi-Parametric Inference for Doubly Stochastic Spatial Point Processes:
  An Approximate Penalized Poisson Likelihood Approach
Semi-Parametric Inference for Doubly Stochastic Spatial Point Processes: An Approximate Penalized Poisson Likelihood Approach
Si Cheng
J. Wakefield
Ali Shojaie
40
0
0
11 Jun 2023
FAStEN: an efficient adaptive method for feature selection and
  estimation in high-dimensional functional regressions
FAStEN: an efficient adaptive method for feature selection and estimation in high-dimensional functional regressions
Tobia Boschi
Lorenzo Testa
Francesca Chiaromonte
M. Reimherr
47
6
0
26 Mar 2023
Testing for the Important Components of Posterior Predictive Variance
Testing for the Important Components of Posterior Predictive Variance
Dean Dustin
B. Clarke
12
2
0
01 Sep 2022
Rotation to Sparse Loadings using $L^p$ Losses and Related Inference
  Problems
Rotation to Sparse Loadings using LpL^pLp Losses and Related Inference Problems
Xinyi Liu
Gabriel Wallin
Yunxiao Chen
I. Moustaki
40
3
0
05 Jun 2022
Subset selection for linear mixed models
Subset selection for linear mixed models
Daniel R. Kowal
72
3
0
27 Jul 2021
Inference in High-dimensional Linear Regression
Inference in High-dimensional Linear Regression
Heather S. Battey
Nancy Reid
49
5
0
22 Jun 2021
Bayesian subset selection and variable importance for interpretable
  prediction and classification
Bayesian subset selection and variable importance for interpretable prediction and classification
Daniel R. Kowal
103
10
0
20 Apr 2021
Time-Invariance Coefficients Tests with the Adaptive Multi-Factor Model
Time-Invariance Coefficients Tests with the Adaptive Multi-Factor Model
Liao Zhu
R. Jarrow
M. Wells
36
14
0
09 Nov 2020
Survival Modeling of Suicide Risk with Rare and Uncertain Diagnoses
Survival Modeling of Suicide Risk with Rare and Uncertain Diagnoses
Wenjie Wang
Chongliang Luo
R. Aseltine
Fei Wang
Jun Yan
Kun Chen
CML
29
0
0
05 Sep 2020
An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic
  Net
An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic Net
Tobia Boschi
M. Reimherr
Francesca Chiaromonte
35
3
0
06 Jun 2020
High-Dimensional Estimation, Basis Assets, and the Adaptive Multi-Factor
  Model
High-Dimensional Estimation, Basis Assets, and the Adaptive Multi-Factor Model
Liao Zhu
Sumanta Basu
R. Jarrow
M. Wells
62
24
0
23 Apr 2018
Debiasing the Debiased Lasso with Bootstrap
Debiasing the Debiased Lasso with Bootstrap
Sai Li
72
14
0
09 Nov 2017
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