Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning

7 August 2020

Papers citing "Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning"

27 / 27 papers shown

Title
Assumption-lean inference for generalised linear model parameters S. Vansteelandt O. Dukes CML 73 49 0 15 Jun 2020
Universal Inference Larry A. Wasserman Aaditya Ramdas Sivaraman Balakrishnan 59 146 0 24 Dec 2019
On the minimax optimality and superiority of deep neural network learning over sparse parameter spaces Satoshi Hayakawa Taiji Suzuki 26 48 0 22 May 2019
Characterization of parameters with a mixed bias property A. Rotnitzky Ezequiel Smucler J. M. Robins 41 66 0 07 Apr 2019
Optimal estimation of variance in nonparametric regression with random design Yandi Shen Chao Gao Daniela Witten Fang Han 42 19 0 27 Feb 2019
User-Friendly Covariance Estimation for Heavy-Tailed Distributions Y. Ke Stanislav Minsker Zhao Ren Qiang Sun Wen-Xin Zhou 37 57 0 05 Nov 2018
Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality Taiji Suzuki 113 243 0 18 Oct 2018
Deep Neural Networks for Estimation and Inference M. Farrell Tengyuan Liang S. Misra BDL 121 254 0 26 Sep 2018
Approximation and Estimation for High-Dimensional Deep Learning Networks Andrew R. Barron Jason M. Klusowski 48 59 0 10 Sep 2018
Moving Beyond Sub-Gaussianity in High-Dimensional Statistics: Applications in Covariance Estimation and Linear Regression Arun K. Kuchibhotla Abhishek Chakrabortty 44 108 0 08 Apr 2018
Cross-Fitting and Fast Remainder Rates for Semiparametric Estimation Whitney Newey Jamie Robins 61 147 0 27 Jan 2018
Nonparametric regression using deep neural networks with ReLU activation function Johannes Schmidt-Hieber 159 805 0 22 Aug 2017
Estimation of the covariance structure of heavy-tailed distributions Stanislav Minsker Xiaohan Wei 57 38 0 01 Aug 2017
Semiparametric Efficient Empirical Higher Order Influence Function Estimators Lin Liu Rajarshi Mukherjee Whitney Newey J. M. Robins 49 38 0 22 May 2017
Efficient and Adaptive Linear Regression in Semi-Supervised Settings Abhishek Chakrabortty Tianxi Cai 28 76 0 17 Jan 2017
Bootstrapping and Sample Splitting For High-Dimensional, Assumption-Free Inference Alessandro Rinaldo Larry A. Wasserman M. G'Sell Jing Lei 53 94 0 16 Nov 2016
Generalized Random Forests Susan Athey J. Tibshirani Stefan Wager 161 1,348 0 05 Oct 2016
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 349 18,300 0 27 May 2016
Numerical Implementation of the QuEST Function Olivier Ledoit Michael Wolf 24 70 0 22 Jan 2016
Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model D. Donoho M. Gavish Iain M. Johnstone 78 206 0 04 Nov 2013
Optimal Uniform Convergence Rates for Sieve Nonparametric Instrumental Variables Regression Xiaohong Chen T. Christensen 42 22 0 02 Nov 2013
Optimal Linear Shrinkage Estimator for Large Dimensional Precision Matrix Taras Bodnar Arjun K. Gupta Nestor Parolya 122 52 0 05 Aug 2013
The Bayesian Analysis of Complex, High-Dimensional Models: Can It Be CODA? Yaácov Ritov Peter J. Bickel A. Gamst B. Kleijn 63 28 0 25 Mar 2012
Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain A. Belloni Daniel L. Chen Victor Chernozhukov Christian B. Hansen 145 554 0 21 Oct 2010
Parameter tuning in pointwise adaptation using a propagation approach V. Spokoiny Céline Vial 89 34 0 25 Aug 2009
Higher order influence functions and minimax estimation of nonlinear functionals J. M. Robins Lingling Li E. T. Tchetgen A. van der Vaart 144 241 0 20 May 2008
Effect of mean on variance function estimation in nonparametric regression Lie Wang L. Brown T. Tony Cai M. Levine 197 118 0 04 Apr 2008