Confidence Intervals for High-Dimensional Linear Regression: Minimax Rates and Adaptivity

18 June 2015

T. Tony Cai

Papers citing "Confidence Intervals for High-Dimensional Linear Regression: Minimax Rates and Adaptivity"

37 / 37 papers shown

Title
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning Frederik Hoppe C. M. Verdun Hannah Laus Felix Krahmer Holger Rauhut UQCV 34 1 0 18 Jul 2024
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects Masahiro Kato CML 41 1 0 05 Mar 2024
Sparsified Simultaneous Confidence Intervals for High-Dimensional Linear Models Xiaorui Zhu Yi Qin Peng Wang 18 0 0 14 Jul 2023
Testing Many Zero Restrictions in a High Dimensional Linear Regression Setting Jonathan B. Hill 38 0 0 22 Jan 2023
Uncertainty quantification for sparse Fourier recovery F. Hoppe Felix Krahmer C. M. Verdun Marion I. Menzel Holger Rauhut 31 7 0 30 Dec 2022
Simultaneous Inference in Non-Sparse High-Dimensional Linear Models Yanmei Shi Zhiruo Li Q. Zhang 23 0 0 17 Oct 2022
Finite- and Large- Sample Inference for Model and Coefficients in High-dimensional Linear Regression with Repro Samples P. Wang Min-ge Xie Linjun Zhang 45 5 0 19 Sep 2022
Minimax Rates and Adaptivity in Combining Experimental and Observational Data Shuxiao Chen B. Zhang T. Ye CML 20 22 0 22 Sep 2021
Near-optimal inference in adaptive linear regression K. Khamaru Y. Deshpande Tor Lattimore Lester W. Mackey Martin J. Wainwright 30 16 0 05 Jul 2021
Surrogate Assisted Semi-supervised Inference for High Dimensional Risk Prediction Jue Hou Zijian Guo Tianxi Cai 14 14 0 04 May 2021
Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies Zijian Guo 28 17 0 15 Nov 2020
Sparse Confidence Sets for Normal Mean Models Y. Ning Guang Cheng 32 2 0 17 Aug 2020
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality Changxiao Cai H. Vincent Poor Yuxin Chen 15 23 0 15 Jun 2020
Minimax Semiparametric Learning With Approximate Sparsity Jelena Bradic Victor Chernozhukov Whitney Newey Yinchu Zhu 52 21 0 27 Dec 2019
De-biasing convex regularized estimators and interval estimation in linear models Pierre C. Bellec Cun-Hui Zhang 34 20 0 26 Dec 2019
Online Debiasing for Adaptively Collected High-dimensional Data with Applications to Time Series Analysis Y. Deshpande Adel Javanmard M. Mehrabi AI4TS 39 31 0 04 Nov 2019
How well can we learn large factor models without assuming strong factors? Yinchu Zhu OOD 19 0 0 23 Oct 2019
Double-estimation-friendly inference for high-dimensional misspecified models Rajen Dinesh Shah Peter Buhlmann 26 10 0 24 Sep 2019
Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models Fei Wang Ling Zhou Lu Tang P. Song 25 4 0 04 Aug 2019
Optimal Statistical Inference for Individualized Treatment Effects in High-dimensional Models Tianxi Cai Tony Cai Zijian Guo CML LM&MA 24 13 0 29 Apr 2019
Robust Estimation of Causal Effects via High-Dimensional Covariate Balancing Propensity Score Y. Ning Sida Peng Kosuke Imai 33 87 0 20 Dec 2018
Automatic Debiased Machine Learning of Causal and Structural Effects Victor Chernozhukov Whitney Newey Rahul Singh CML AI4CE 24 103 0 14 Sep 2018
Regression adjustment in completely randomized experiments with a diverging number of covariates Lihua Lei Peng Ding 34 48 0 20 Jun 2018
Semi-supervised Inference for Explained Variance in High-dimensional Linear Regression and Its Applications T. Tony Cai Zijian Guo 24 59 0 16 Jun 2018
A modern maximum-likelihood theory for high-dimensional logistic regression Pragya Sur Emmanuel J. Candes 30 285 0 19 Mar 2018
Fixed effects testing in high-dimensional linear mixed models Jelena Bradic G. Claeskens Thomas Gueuning 25 17 0 14 Aug 2017
Breaking the curse of dimensionality in regression Yinchu Zhu Jelena Bradic 27 19 0 01 Aug 2017
A Flexible Framework for Hypothesis Testing in High-dimensions Adel Javanmard Jason D. Lee 36 29 0 26 Apr 2017
Adaptive estimation of the sparsity in the Gaussian vector model Alexandra Carpentier Nicolas Verzélen 21 29 0 01 Mar 2017
Linear Hypothesis Testing in Dense High-Dimensional Linear Models Yinchu Zhu Jelena Bradic 31 84 0 10 Oct 2016
Testing Endogeneity with High Dimensional Covariates Zijian Guo Hyunseung Kang T. Tony Cai Dylan S. Small 29 24 0 21 Sep 2016
High-dimensional regression adjustments in randomized experiments Stefan Wager Wenfei Du Jonathan E. Taylor Robert Tibshirani 40 117 0 22 Jul 2016
Approximate Residual Balancing: De-Biased Inference of Average Treatment Effects in High Dimensions Susan Athey Guido Imbens Stefan Wager CML 35 387 0 25 Apr 2016
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 30 118 0 16 Mar 2016
Optimal inference in a class of regression models Timothy B. Armstrong M. Kolesár 24 125 0 19 Nov 2015
A Unified Theory of Confidence Regions and Testing for High Dimensional Estimating Equations Matey Neykov Y. Ning Jun S. Liu Han Liu 34 77 0 30 Oct 2015
Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory Adel Javanmard Andrea Montanari 117 160 0 17 Jan 2013