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Hypothesis Testing in High-Dimensional Regression under the Gaussian
  Random Design Model: Asymptotic Theory

Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory

17 January 2013
Adel Javanmard
Andrea Montanari
ArXivPDFHTML

Papers citing "Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory"

22 / 22 papers shown
Title
Inference on Optimal Dynamic Policies via Softmax Approximation
Inference on Optimal Dynamic Policies via Softmax Approximation
Qizhao Chen
Morgane Austern
Vasilis Syrgkanis
OffRL
29
1
0
08 Mar 2023
Uncertainty quantification for sparse Fourier recovery
Uncertainty quantification for sparse Fourier recovery
F. Hoppe
Felix Krahmer
C. M. Verdun
Marion I. Menzel
Holger Rauhut
27
7
0
30 Dec 2022
LASSO risk and phase transition under dependence
LASSO risk and phase transition under dependence
Hanwen Huang
35
3
0
30 Mar 2021
Distributed Bootstrap for Simultaneous Inference Under High
  Dimensionality
Distributed Bootstrap for Simultaneous Inference Under High Dimensionality
Yang Yu
Shih-Kang Chao
Guang Cheng
FedML
32
10
0
19 Feb 2021
Estimation, Confidence Intervals, and Large-Scale Hypotheses Testing for
  High-Dimensional Mixed Linear Regression
Estimation, Confidence Intervals, and Large-Scale Hypotheses Testing for High-Dimensional Mixed Linear Regression
Linjun Zhang
Rong Ma
T. Tony Cai
Hongzhe Li
44
12
0
06 Nov 2020
The Lasso with general Gaussian designs with applications to hypothesis
  testing
The Lasso with general Gaussian designs with applications to hypothesis testing
Michael Celentano
Andrea Montanari
Yuting Wei
42
63
0
27 Jul 2020
De-biasing convex regularized estimators and interval estimation in
  linear models
De-biasing convex regularized estimators and interval estimation in linear models
Pierre C. Bellec
Cun-Hui Zhang
21
20
0
26 Dec 2019
Online Debiasing for Adaptively Collected High-dimensional Data with
  Applications to Time Series Analysis
Online Debiasing for Adaptively Collected High-dimensional Data with Applications to Time Series Analysis
Y. Deshpande
Adel Javanmard
M. Mehrabi
AI4TS
28
31
0
04 Nov 2019
Power analysis of knockoff filters for correlated designs
Power analysis of knockoff filters for correlated designs
Jingbo Liu
Philippe Rigollet
20
16
0
28 Oct 2019
Efficient Estimation of Smooth Functionals in Gaussian Shift Models
Efficient Estimation of Smooth Functionals in Gaussian Shift Models
V. Koltchinskii
M. Zhilova
20
14
0
05 Oct 2018
Automatic Debiased Machine Learning of Causal and Structural Effects
Automatic Debiased Machine Learning of Causal and Structural Effects
Victor Chernozhukov
Whitney Newey
Rahul Singh
CML
AI4CE
16
103
0
14 Sep 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
15
59
0
16 Jun 2018
A modern maximum-likelihood theory for high-dimensional logistic
  regression
A modern maximum-likelihood theory for high-dimensional logistic regression
Pragya Sur
Emmanuel J. Candes
23
285
0
19 Mar 2018
In Defense of the Indefensible: A Very Naive Approach to
  High-Dimensional Inference
In Defense of the Indefensible: A Very Naive Approach to High-Dimensional Inference
Sen Zhao
Daniela Witten
Ali Shojaie
39
57
0
16 May 2017
Online Rules for Control of False Discovery Rate and False Discovery
  Exceedance
Online Rules for Control of False Discovery Rate and False Discovery Exceedance
Adel Javanmard
Andrea Montanari
14
105
0
29 Mar 2016
Universality laws for randomized dimension reduction, with applications
Universality laws for randomized dimension reduction, with applications
Samet Oymak
J. Tropp
46
109
0
30 Nov 2015
Uniform Asymptotic Inference and the Bootstrap After Model Selection
Uniform Asymptotic Inference and the Bootstrap After Model Selection
R. Tibshirani
Alessandro Rinaldo
Robert Tibshirani
Larry A. Wasserman
29
104
0
20 Jun 2015
Inference of high-dimensional linear models with time-varying
  coefficients
Inference of high-dimensional linear models with time-varying coefficients
Xiaohui Chen
Yifeng He
39
9
0
12 Jun 2015
The Benefit of Group Sparsity in Group Inference with De-biased Scaled
  Group Lasso
The Benefit of Group Sparsity in Group Inference with De-biased Scaled Group Lasso
Ritwik Mitra
Cun-Hui Zhang
39
46
0
13 Dec 2014
Optimal Inference After Model Selection
Optimal Inference After Model Selection
William Fithian
Dennis L. Sun
Jonathan E. Taylor
32
332
0
09 Oct 2014
On asymptotically optimal confidence regions and tests for
  high-dimensional models
On asymptotically optimal confidence regions and tests for high-dimensional models
Sara van de Geer
Peter Buhlmann
Yaácov Ritov
Ruben Dezeure
46
1,128
0
03 Mar 2013
A significance test for the lasso
A significance test for the lasso
R. Lockhart
Jonathan E. Taylor
R. Tibshirani
Robert Tibshirani
61
656
0
30 Jan 2013
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