ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1711.03613
  4. Cited By
Debiasing the Debiased Lasso with Bootstrap
v1v2 (latest)

Debiasing the Debiased Lasso with Bootstrap

9 November 2017
Sai Li
ArXiv (abs)PDFHTML

Papers citing "Debiasing the Debiased Lasso with Bootstrap"

8 / 8 papers shown
Debiased high-dimensional regression calibration for errors-in-variables
  log-contrast models
Debiased high-dimensional regression calibration for errors-in-variables log-contrast models
Huali Zhao
Tianying Wang
164
1
0
11 Sep 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
313
2
0
18 Jul 2024
High-Dimensional Confidence Regions in Sparse MRI
High-Dimensional Confidence Regions in Sparse MRI
Frederik Hoppe
Felix Krahmer
C. M. Verdun
Marion I. Menzel
Holger Rauhut
258
6
0
18 Jul 2024
Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty
Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty
Kaizhao Liu
Jose H. Blanchet
Lexing Ying
Yiping Lu
334
2
0
29 Apr 2024
Uncertainty quantification for sparse Fourier recovery
Uncertainty quantification for sparse Fourier recovery
F. Hoppe
Felix Krahmer
C. M. Verdun
Marion I. Menzel
Holger Rauhut
358
7
0
30 Dec 2022
DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural
  Networks
DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural NetworksInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Shiyun Xu
Zhiqi Bu
304
1
0
01 Nov 2020
Honest confidence sets for high-dimensional regression by projection and
  shrinkage
Honest confidence sets for high-dimensional regression by projection and shrinkageJournal of the American Statistical Association (JASA), 2019
Kun Zhou
Ker-Chau Li
Qing Zhou
348
4
0
01 Feb 2019
On the Properties of Simulation-based Estimators in High Dimensions
On the Properties of Simulation-based Estimators in High Dimensions
S. Guerrier
Mucyo Karemera
Samuel Orso
Maria-Pia Victoria-Feser
282
2
0
10 Oct 2018
1
Page 1 of 1