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On asymptotically optimal confidence regions and tests for
  high-dimensional models
v1v2v3 (latest)

On asymptotically optimal confidence regions and tests for high-dimensional models

3 March 2013
Sara van de Geer
Peter Buhlmann
Yaácov Ritov
Ruben Dezeure
ArXiv (abs)PDFHTML

Papers citing "On asymptotically optimal confidence regions and tests for high-dimensional models"

50 / 386 papers shown
Title
PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework
PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework
Abhineet Agarwal
Michael Xiao
Rebecca L. Barter
Omer Ronen
Boyu Fan
Bin Yu
72
0
0
13 May 2025
Extended Fiducial Inference for Individual Treatment Effects via Deep Neural Networks
Extended Fiducial Inference for Individual Treatment Effects via Deep Neural Networks
Sehwan Kim
F. Liang
FedML
93
0
0
04 May 2025
Statistically Testing Training Data for Unwanted Error Patterns using Rule-Oriented Regression
Statistically Testing Training Data for Unwanted Error Patterns using Rule-Oriented Regression
Stefan Rass
Martin Dallinger
102
0
0
24 Mar 2025
Fast Debiasing of the LASSO Estimator
Fast Debiasing of the LASSO Estimator
Shuvayan Banerjee
James Saunderson
Radhendushka Srivastava
Ajit V. Rajwade
79
0
0
27 Feb 2025
Robust Inference for High-dimensional Linear Models with Heavy-tailed
  Errors via Partial Gini Covariance
Robust Inference for High-dimensional Linear Models with Heavy-tailed Errors via Partial Gini Covariance
Yilin Zhang
Songshan Yang
Y. Wu
Lan Wang
99
0
0
19 Nov 2024
Debiased Regression for Root-N-Consistent Conditional Mean Estimation
Masahiro Kato
113
0
0
18 Nov 2024
Statistical Inference on High Dimensional Gaussian Graphical Regression
  Models
Statistical Inference on High Dimensional Gaussian Graphical Regression Models
Xuran Meng
Jingfei Zhang
Yi Li
74
1
0
03 Nov 2024
Statistical Inference in High-dimensional Poisson Regression with
  Applications to Mediation Analysis
Statistical Inference in High-dimensional Poisson Regression with Applications to Mediation Analysis
Prabrisha Rakshit
Zijian Guo
45
1
0
28 Oct 2024
Statistical Inference in Classification of High-dimensional Gaussian
  Mixture
Statistical Inference in Classification of High-dimensional Gaussian Mixture
Hanwen Huang
Peng Zeng
49
0
0
25 Oct 2024
High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching
High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching
Daniel J. Williams
Leyang Wang
Qizhen Ying
Song Liu
Mladen Kolar
116
2
0
14 Oct 2024
Interval Estimation of Coefficients in Penalized Regression Models of Insurance Data
Interval Estimation of Coefficients in Penalized Regression Models of Insurance Data
Alokesh Manna
Zijian Huang
Dipak K. Dey
Yuwen Gu
Robin He
91
1
0
01 Oct 2024
Automatic debiasing of neural networks via moment-constrained learning
Automatic debiasing of neural networks via moment-constrained learning
Christian L. Hines
Oliver J. Hines
CMLOOD
158
0
0
29 Sep 2024
Double-Estimation-Friendly Inference for High Dimensional Misspecified
  Measurement Error Models
Double-Estimation-Friendly Inference for High Dimensional Misspecified Measurement Error Models
Shijie Cui
Xu Guo
Runze Li
Songshan Yang
Zhe Zhang
39
0
0
24 Sep 2024
Debiased high-dimensional regression calibration for errors-in-variables
  log-contrast models
Debiased high-dimensional regression calibration for errors-in-variables log-contrast models
Huali Zhao
Tianying Wang
41
1
0
11 Sep 2024
U-learning for Prediction Inference via Combinatory Multi-Subsampling:
  With Applications to LASSO and Neural Networks
U-learning for Prediction Inference via Combinatory Multi-Subsampling: With Applications to LASSO and Neural Networks
Zhe Fei
Yi Li
AI4CE
73
1
0
22 Jul 2024
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning
Frederik Hoppe
C. M. Verdun
Hannah Laus
Felix Krahmer
Holger Rauhut
UQCV
92
1
0
18 Jul 2024
High-Dimensional Confidence Regions in Sparse MRI
High-Dimensional Confidence Regions in Sparse MRI
Frederik Hoppe
Felix Krahmer
C. M. Verdun
Marion I. Menzel
Holger Rauhut
72
5
0
18 Jul 2024
With or Without Replacement? Improving Confidence in Fourier Imaging
With or Without Replacement? Improving Confidence in Fourier Imaging
Frederik Hoppe
C. M. Verdun
Felix Krahmer
Marion I. Menzel
Holger Rauhut
59
0
0
18 Jul 2024
A variational Bayes approach to debiased inference for low-dimensional
  parameters in high-dimensional linear regression
A variational Bayes approach to debiased inference for low-dimensional parameters in high-dimensional linear regression
Ismaël Castillo
Alice L'Huillier
Kolyan Ray
Luke Travis
67
0
0
18 Jun 2024
Adaptive debiased SGD in high-dimensional GLMs with streaming data
Adaptive debiased SGD in high-dimensional GLMs with streaming data
Ruijian Han
Lan Luo
Yuanhang Luo
Yuanyuan Lin
Jian Huang
156
0
0
28 May 2024
Transfer Learning Under High-Dimensional Graph Convolutional Regression
  Model for Node Classification
Transfer Learning Under High-Dimensional Graph Convolutional Regression Model for Node Classification
Jiachen Chen
Danyang Huang
Liyuan Wang
Kathryn L. Lunetta
Debarghya Mukherjee
Huimin Cheng
58
0
0
26 May 2024
Inference with non-differentiable surrogate loss in a general
  high-dimensional classification framework
Inference with non-differentiable surrogate loss in a general high-dimensional classification framework
Muxuan Liang
Yang Ning
Maureen A Smith
Yingqi Zhao
43
0
0
20 May 2024
Stability of a Generalized Debiased Lasso with Applications to
  Resampling-Based Variable Selection
Stability of a Generalized Debiased Lasso with Applications to Resampling-Based Variable Selection
Jingbo Liu
73
0
0
05 May 2024
Covariance Regression with High-Dimensional Predictors
Covariance Regression with High-Dimensional Predictors
Yuheng He
Changliang Zou
Yi Zhao
48
0
0
10 Apr 2024
Learning Directed Acyclic Graphs from Partial Orderings
Learning Directed Acyclic Graphs from Partial Orderings
Ali Shojaie
Wenyu Chen
CML
89
0
0
24 Mar 2024
The Wreaths of KHAN: Uniform Graph Feature Selection with False
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The Wreaths of KHAN: Uniform Graph Feature Selection with False Discovery Rate Control
Jiajun Liang
Yue Liu
Doudou Zhou
Sinian Zhang
Junwei Lu
115
0
0
18 Mar 2024
Triple/Debiased Lasso for Statistical Inference of Conditional Average
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Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects
Masahiro Kato
CML
77
1
0
05 Mar 2024
Applied Causal Inference Powered by ML and AI
Applied Causal Inference Powered by ML and AI
Victor Chernozhukov
Christian Hansen
Nathan Kallus
Martin Spindler
Vasilis Syrgkanis
CML
84
32
0
04 Mar 2024
High-Dimensional Tail Index Regression: with An Application to Text
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High-Dimensional Tail Index Regression: with An Application to Text Analyses of Viral Posts in Social Media
Yuya Sasaki
Jing Tao
Yulong Wang
62
0
0
02 Mar 2024
Debiased LASSO under Poisson-Gauss Model
Debiased LASSO under Poisson-Gauss Model
Pedro Abdalla
Gil Kur
46
0
0
26 Feb 2024
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
Jikai Jin
Vasilis Syrgkanis
CML
219
1
0
22 Feb 2024
A structured regression approach for evaluating model performance across
  intersectional subgroups
A structured regression approach for evaluating model performance across intersectional subgroups
Christine Herlihy
Kimberly Truong
Alexandra Chouldechova
Miroslav Dudik
72
5
0
26 Jan 2024
Distributional Robustness and Transfer Learning Through Empirical Bayes
Distributional Robustness and Transfer Learning Through Empirical Bayes
Michael Law
Peter Bühlmann
Yaácov Ritov
OOD
44
0
0
13 Dec 2023
CATE Lasso: Conditional Average Treatment Effect Estimation with
  High-Dimensional Linear Regression
CATE Lasso: Conditional Average Treatment Effect Estimation with High-Dimensional Linear Regression
Masahiro Kato
Masaaki Imaizumi
CML
68
2
0
25 Oct 2023
On Adaptive confidence Ellipsoids for sparse high dimensional linear
  models
On Adaptive confidence Ellipsoids for sparse high dimensional linear models
Xiaoyang Xie
45
0
0
24 Oct 2023
Sequential Gibbs Posteriors with Applications to Principal Component
  Analysis
Sequential Gibbs Posteriors with Applications to Principal Component Analysis
Steven Winter
Omar Melikechi
David B. Dunson
74
2
0
19 Oct 2023
Uncertainty quantification for learned ISTA
Uncertainty quantification for learned ISTA
Frederik Hoppe
C. M. Verdun
Felix Krahmer
Hannah Laus
Holger Rauhut
UQCV
78
4
0
14 Sep 2023
Interpretable Machine Learning for Discovery: Statistical Challenges \&
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Interpretable Machine Learning for Discovery: Statistical Challenges \& Opportunities
Genevera I. Allen
Luqin Gan
Lili Zheng
89
9
0
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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
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0
24 Jul 2023
Sparsified Simultaneous Confidence Intervals for High-Dimensional Linear Models
Sparsified Simultaneous Confidence Intervals for High-Dimensional Linear Models
Xiaorui Zhu
Yi Qin
Peng Wang
80
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Information criteria for structured parameter selection in high
  dimensional tree and graph models
Information criteria for structured parameter selection in high dimensional tree and graph models
M. Jansen
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A Model-free Closeness-of-influence Test for Features in Supervised
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A Model-free Closeness-of-influence Test for Features in Supervised Learning
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Ryan A. Rossi
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Distributed Semi-Supervised Sparse Statistical Inference
Distributed Semi-Supervised Sparse Statistical Inference
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Weidong Liu
Xiaojun Mao
Mingyue Xu
46
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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
89
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A parametric distribution for exact post-selection inference with data
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A parametric distribution for exact post-selection inference with data carving
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47
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Root-n consistent semiparametric learning with high-dimensional nuisance
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Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity
Lin Liu
Yuhao Wang
72
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Penalized Likelihood Inference with Survey Data
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J. Jasiak
Purevdorj Tuvaandorj
40
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Inference on Optimal Dynamic Policies via Softmax Approximation
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Qizhao Chen
Morgane Austern
Vasilis Syrgkanis
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71
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Communication-Efficient Distributed Estimation and Inference for Cox's
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Jianqing Fan
Zhipeng Lou
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Statistical Inference and Large-scale Multiple Testing for
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Zijian Guo
Yin Xia
106
7
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