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Doubly Debiased Lasso: High-Dimensional Inference under Hidden
  Confounding
v1v2v3 (latest)

Doubly Debiased Lasso: High-Dimensional Inference under Hidden Confounding

Annals of Statistics (Ann. Stat.), 2020
8 April 2020
Zijian Guo
Domagoj Cevid
Peter Buhlmann
    CML
ArXiv (abs)PDFHTML

Papers citing "Doubly Debiased Lasso: High-Dimensional Inference under Hidden Confounding"

13 / 13 papers shown
Deconfounded Warm-Start Thompson Sampling with Applications to Precision Medicine
Deconfounded Warm-Start Thompson Sampling with Applications to Precision Medicine
Prateek Jaiswal
Esmaeil Keyvanshokooh
Junyu Cao
307
0
0
22 May 2025
Ice Cream Doesn't Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference
Ice Cream Doesn't Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference
Jin Du
Li Chen
Xun Xian
An Luo
Fangqiao Tian
Ganghua Wang
Charles Doss
Xiaotong Shen
Jie Ding
CMLELM
224
1
0
19 May 2025
ExMAG: Learning of Maximally Ancestral Graphs
ExMAG: Learning of Maximally Ancestral Graphs
Petr Rysavý
Pavel Rytíř
Xiaoyu He
Georgios Korpas
Georgios Korpas
CML
566
1
0
11 Mar 2025
Double Machine Learning for Adaptive Causal Representation in
  High-Dimensional Data
Double Machine Learning for Adaptive Causal Representation in High-Dimensional Data
Lynda Aouar
Han Yu
CML
401
0
0
22 Nov 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
343
4
0
18 Jul 2024
Substitute adjustment via recovery of latent variables
Substitute adjustment via recovery of latent variables
Jeffrey Adams
Niels Richard Hansen
CML
280
2
0
01 Mar 2024
Simultaneous inference for generalized linear models with unmeasured confounders
Simultaneous inference for generalized linear models with unmeasured confounders
Jin-Hong Du
Larry Wasserman
Kathryn Roeder
568
10
0
13 Sep 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
291
9
0
25 Jan 2023
Asymptotic normality in linear regression with approximately sparse
  structure
Asymptotic normality in linear regression with approximately sparse structure
Saulius Jokubaitis
R. Leipus
206
1
0
08 Mar 2022
Correcting Confounding via Random Selection of Background Variables
Correcting Confounding via Random Selection of Background Variables
You-Lin Chen
Lenon Minorics
Dominik Janzing
CML
231
4
0
04 Feb 2022
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
611
2
0
27 Oct 2020
Deconfounding and Causal Regularization for Stability and External
  Validity
Deconfounding and Causal Regularization for Stability and External Validity
Peter Buhlmann
Domagoj Cevid
CML
243
13
0
14 Aug 2020
Naïve regression requires weaker assumptions than factor models to
  adjust for multiple cause confounding
Naïve regression requires weaker assumptions than factor models to adjust for multiple cause confoundingJournal of machine learning research (JMLR), 2020
Justin Grimmer
D. Knox
Brandon M Stewart
CML
285
13
0
24 Jul 2020
1
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