ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1908.05607
  4. Cited By
Efficient Estimation of Pathwise Differentiable Target Parameters with
  the Undersmoothed Highly Adaptive Lasso
v1v2 (latest)

Efficient Estimation of Pathwise Differentiable Target Parameters with the Undersmoothed Highly Adaptive Lasso

14 August 2019
M. J. van der Laan
David Benkeser
Weixin Cai
ArXiv (abs)PDFHTML

Papers citing "Efficient Estimation of Pathwise Differentiable Target Parameters with the Undersmoothed Highly Adaptive Lasso"

9 / 9 papers shown
Title
Constructing Confidence Intervals for Average Treatment Effects from
  Multiple Datasets
Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets
Yuxin Wang
Maresa Schröder
Dennis Frauen
Jonas Schweisthal
Konstantin Hess
Stefan Feuerriegel
CML
181
3
0
16 Dec 2024
Adaptive-TMLE for the Average Treatment Effect based on Randomized Controlled Trial Augmented with Real-World Data
Adaptive-TMLE for the Average Treatment Effect based on Randomized Controlled Trial Augmented with Real-World Data
Mark van der Laan
Sky Qiu
L. Laan
Lars van der Laan
92
9
0
12 May 2024
Adaptive debiased machine learning using data-driven model selection
  techniques
Adaptive debiased machine learning using data-driven model selection techniques
L. Laan
M. Carone
Alexander Luedtke
Mark van der Laan
74
9
0
24 Jul 2023
Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing
  without Influence Functions for Many Target Parameters
Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters
Brian M Cho
Yaroslav Mukhin
Kyra Gan
Ivana Malenica
89
2
0
14 Jun 2023
Lassoed Tree Boosting
Lassoed Tree Boosting
Alejandro Schuler
Yi Li
Mark van der Laan
114
3
0
22 May 2022
Why Machine Learning Cannot Ignore Maximum Likelihood Estimation
Why Machine Learning Cannot Ignore Maximum Likelihood Estimation
Mark van der Laan
Sherri Rose
OOD
46
2
0
23 Oct 2021
Estimation of population size based on capture recapture designs and
  evaluation of the estimation reliability
Estimation of population size based on capture recapture designs and evaluation of the estimation reliability
Yue You
Mark van der Laan
P. Collender
Qu Cheng
A. Hubbard
N. Jewell
Zhibo Hu
R. Mejia
J. Remais
24
4
0
12 May 2021
Nonparametric inverse probability weighted estimators based on the
  highly adaptive lasso
Nonparametric inverse probability weighted estimators based on the highly adaptive lasso
Ashkan Ertefaie
N. Hejazi
M. J. van der Laan
135
24
0
22 May 2020
Universal sieve-based strategies for efficient estimation using machine
  learning tools
Universal sieve-based strategies for efficient estimation using machine learning tools
Hongxiang Qiu
Alexander Luedtke
M. Carone
51
6
0
04 Mar 2020
1