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Cross-Fitting and Fast Remainder Rates for Semiparametric Estimation

Cross-Fitting and Fast Remainder Rates for Semiparametric Estimation

27 January 2018
Whitney Newey
Jamie Robins
ArXivPDFHTML

Papers citing "Cross-Fitting and Fast Remainder Rates for Semiparametric Estimation"

50 / 67 papers shown
Title
AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis
AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis
Haroui Ma
Francesco Quinzan
Theresa Willem
Stefan Bauer
76
0
0
28 Apr 2025
Semiparametric Counterfactual Regression
Semiparametric Counterfactual Regression
Kwangho Kim
OffRL
31
0
0
03 Apr 2025
Targeted Learning for Variable Importance
Targeted Learning for Variable Importance
Xiaohan Wang
Yunzhe Zhou
Giles Hooker
28
0
0
04 Nov 2024
Assumption-Lean Post-Integrated Inference with Negative Control Outcomes
Assumption-Lean Post-Integrated Inference with Negative Control Outcomes
Jin-Hong Du
Kathryn Roeder
Larry Wasserman
39
1
0
07 Oct 2024
Performance of Cross-Validated Targeted Maximum Likelihood Estimation
Performance of Cross-Validated Targeted Maximum Likelihood Estimation
Matthew J. Smith
Rachael V. Phillips
C. Maringe
Miguel Angel Luque-Fernandez
31
1
0
17 Sep 2024
Multiply-Robust Causal Change Attribution
Multiply-Robust Causal Change Attribution
Victor Quintas-Martinez
M. T. Bahadori
Eduardo Santiago
Jeff Mu
Dominik Janzing
David Heckerman
CML
29
1
0
12 Apr 2024
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits
Muhammad Faaiz Taufiq
Arnaud Doucet
Rob Cornish
Jean-François Ton
OffRL
24
7
0
03 Dec 2023
Optimally weighted average derivative effects
Optimally weighted average derivative effects
Oliver Hines
Karla Diaz-Ordaz
S. Vansteelandt
CML
26
2
0
10 Aug 2023
RCT Rejection Sampling for Causal Estimation Evaluation
RCT Rejection Sampling for Causal Estimation Evaluation
Katherine A. Keith
Sergey Feldman
David Jurgens
Jonathan Bragg
Rohit Bhattacharya
CML
27
7
0
27 Jul 2023
The Connection Between R-Learning and Inverse-Variance Weighting for
  Estimation of Heterogeneous Treatment Effects
The Connection Between R-Learning and Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
Aaron Fisher
CML
16
1
0
19 Jul 2023
Assumption-lean falsification tests of rate double-robustness of
  double-machine-learning estimators
Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators
Lin Liu
Rajarshi Mukherjee
J. M. Robins
24
1
0
18 Jun 2023
Three-way Cross-Fitting and Pseudo-Outcome Regression for Estimation of
  Conditional Effects and other Linear Functionals
Three-way Cross-Fitting and Pseudo-Outcome Regression for Estimation of Conditional Effects and other Linear Functionals
Aaron Fisher
Virginia Fisher
16
3
0
12 Jun 2023
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy
  Learning
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning
K. Kim
J. Zubizarreta
26
6
0
06 Jun 2023
Off-Policy Evaluation for Large Action Spaces via Conjunct Effect
  Modeling
Off-Policy Evaluation for Large Action Spaces via Conjunct Effect Modeling
Yuta Saito
Qingyang Ren
Thorsten Joachims
CML
OffRL
19
22
0
14 May 2023
The Fundamental Limits of Structure-Agnostic Functional Estimation
The Fundamental Limits of Structure-Agnostic Functional Estimation
Sivaraman Balakrishnan
Edward H. Kennedy
Larry A. Wasserman
20
11
0
06 May 2023
Augmented balancing weights as linear regression
Augmented balancing weights as linear regression
David Bruns-Smith
O. Dukes
Avi Feller
Elizabeth L. Ogburn
27
10
0
27 Apr 2023
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
Causal isotonic calibration for heterogeneous treatment effects
Causal isotonic calibration for heterogeneous treatment effects
L. Laan
Ernesto Ulloa-Pérez
M. Carone
Alexander Luedtke
19
11
0
27 Feb 2023
New $\sqrt{n}$-consistent, numerically stable higher-order influence
  function estimators
New n\sqrt{n}n​-consistent, numerically stable higher-order influence function estimators
Lin Liu
Chang Li
13
0
0
16 Feb 2023
Doubly Robust Counterfactual Classification
Doubly Robust Counterfactual Classification
K. Kim
Edward H. Kennedy
J. Zubizarreta
OffRL
33
5
0
15 Jan 2023
Rank-transformed subsampling: inference for multiple data splitting and
  exchangeable p-values
Rank-transformed subsampling: inference for multiple data splitting and exchangeable p-values
F. R. Guo
Rajen Dinesh Shah
19
14
0
06 Jan 2023
Finite-Sample Guarantees for High-Dimensional DML
Finite-Sample Guarantees for High-Dimensional DML
Victor Quintas-Martinez
AI4CE
26
1
0
15 Jun 2022
Calibration Error for Heterogeneous Treatment Effects
Calibration Error for Heterogeneous Treatment Effects
Yizhe Xu
Steve Yadlowsky
31
12
0
24 Mar 2022
T-Cal: An optimal test for the calibration of predictive models
T-Cal: An optimal test for the calibration of predictive models
Donghwan Lee
Xinmeng Huang
Hamed Hassani
Edgar Dobriban
22
20
0
03 Mar 2022
Differentially Private Estimation of Heterogeneous Causal Effects
Differentially Private Estimation of Heterogeneous Causal Effects
Fengshi Niu
Harsha Nori
B. Quistorff
R. Caruana
Donald Ngwe
A. Kannan
CML
17
13
0
22 Feb 2022
Off-Policy Evaluation for Large Action Spaces via Embeddings
Off-Policy Evaluation for Large Action Spaces via Embeddings
Yuta Saito
Thorsten Joachims
OffRL
25
43
0
13 Feb 2022
A nonparametric doubly robust test for a continuous treatment effect
A nonparametric doubly robust test for a continuous treatment effect
Charles R. Doss
Guangwei Weng
Lan Wang
I. Moscovice
T. Chantarat
17
1
0
07 Feb 2022
Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit
  Performance
Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance
Gabriel Okasa
CML
19
6
0
30 Jan 2022
Semi-Supervised Quantile Estimation: Robust and Efficient Inference in
  High Dimensional Settings
Semi-Supervised Quantile Estimation: Robust and Efficient Inference in High Dimensional Settings
Abhishek Chakrabortty
Guorong Dai
Ray Carroll
11
8
0
25 Jan 2022
Local permutation tests for conditional independence
Local permutation tests for conditional independence
Ilmun Kim
Matey Neykov
Sivaraman Balakrishnan
Larry A. Wasserman
13
27
0
22 Dec 2021
Decorrelated Variable Importance
Decorrelated Variable Importance
I. Verdinelli
Larry A. Wasserman
FAtt
15
17
0
21 Nov 2021
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with
  Neural Nets and Random Forests
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
Victor Chernozhukov
Whitney Newey
Victor Quintas-Martinez
Vasilis Syrgkanis
CML
13
36
0
06 Oct 2021
Parameterising the effect of a continuous exposure using average
  derivative effects
Parameterising the effect of a continuous exposure using average derivative effects
Oliver Hines
Karla Diaz-Ordaz
S. Vansteelandt
14
10
0
27 Sep 2021
Semiparametric Estimation of Long-Term Treatment Effects
Semiparametric Estimation of Long-Term Treatment Effects
Jiafeng Chen
David M. Ritzwoller
28
19
0
30 Jul 2021
Machine Learning for Variance Reduction in Online Experiments
Machine Learning for Variance Reduction in Online Experiments
Yongyi Guo
Dominic Coey
Mikael Konutgan
Wenting Li
Ch. P. Schoener
Matt Goldman
14
34
0
14 Jun 2021
Automatic Debiased Machine Learning via Riesz Regression
Automatic Debiased Machine Learning via Riesz Regression
Victor Chernozhukov
Whitney Newey
Victor Quintas-Martinez
Vasilis Syrgkanis
OOD
CML
15
4
0
30 Apr 2021
Cross-validation: what does it estimate and how well does it do it?
Cross-validation: what does it estimate and how well does it do it?
Stephen Bates
Trevor Hastie
Robert Tibshirani
UQCV
17
269
0
01 Apr 2021
Orthogonalized Kernel Debiased Machine Learning for Multimodal Data
  Analysis
Orthogonalized Kernel Debiased Machine Learning for Multimodal Data Analysis
Xiaowu Dai
Lexin Li
11
10
0
12 Mar 2021
Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile
  Balancing
Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing
Jacob Dorn
Kevin Guo
17
57
0
08 Feb 2021
Deep Learning for Individual Heterogeneity
Deep Learning for Individual Heterogeneity
M. Farrell
Tengyuan Liang
S. Misra
BDL
29
0
0
28 Oct 2020
Estimating Structural Target Functions using Machine Learning and
  Influence Functions
Estimating Structural Target Functions using Machine Learning and Influence Functions
Alicia Curth
Ahmed Alaa
M. Schaar
CML
TDI
11
3
0
14 Aug 2020
Rejoinder: On nearly assumption-free tests of nominal confidence
  interval coverage for causal parameters estimated by machine learning
Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning
Lin Liu
Rajarshi Mukherjee
J. M. Robins
CML
33
16
0
07 Aug 2020
Assumption-lean inference for generalised linear model parameters
Assumption-lean inference for generalised linear model parameters
S. Vansteelandt
O. Dukes
CML
21
49
0
15 Jun 2020
Towards optimal doubly robust estimation of heterogeneous causal effects
Towards optimal doubly robust estimation of heterogeneous causal effects
Edward H. Kennedy
CML
9
308
0
29 Apr 2020
Machine learning for causal inference: on the use of cross-fit
  estimators
Machine learning for causal inference: on the use of cross-fit estimators
P. Zivich
A. Breskin
CML
OOD
11
63
0
21 Apr 2020
On the role of surrogates in the efficient estimation of treatment
  effects with limited outcome data
On the role of surrogates in the efficient estimation of treatment effects with limited outcome data
Nathan Kallus
Xiaojie Mao
11
58
0
27 Mar 2020
Debiased Off-Policy Evaluation for Recommendation Systems
Debiased Off-Policy Evaluation for Recommendation Systems
Yusuke Narita
Shota Yasui
Kohei Yata
OffRL
10
11
0
20 Feb 2020
Minimax Semiparametric Learning With Approximate Sparsity
Minimax Semiparametric Learning With Approximate Sparsity
Jelena Bradic
Victor Chernozhukov
Whitney Newey
Yinchu Zhu
47
21
0
27 Dec 2019
High Dimensional M-Estimation with Missing Outcomes: A Semi-Parametric
  Framework
High Dimensional M-Estimation with Missing Outcomes: A Semi-Parametric Framework
Abhishek Chakrabortty
Jiarui Lu
T. Tony Cai
Hongzhe Li
14
6
0
26 Nov 2019
How well can we learn large factor models without assuming strong
  factors?
How well can we learn large factor models without assuming strong factors?
Yinchu Zhu
OOD
14
0
0
23 Oct 2019
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