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Bootstrapping and Sample Splitting For High-Dimensional, Assumption-Free
  Inference

Bootstrapping and Sample Splitting For High-Dimensional, Assumption-Free Inference

16 November 2016
Alessandro Rinaldo
Larry A. Wasserman
M. G'Sell
Jing Lei
ArXivPDFHTML

Papers citing "Bootstrapping and Sample Splitting For High-Dimensional, Assumption-Free Inference"

13 / 13 papers shown
Title
EvGNN: An Event-driven Graph Neural Network Accelerator for Edge Vision
EvGNN: An Event-driven Graph Neural Network Accelerator for Edge Vision
Yufeng Yang
Adrian Kneip
Charlotte Frenkel
GNN
28
4
0
30 Apr 2024
The Limits of Assumption-free Tests for Algorithm Performance
The Limits of Assumption-free Tests for Algorithm Performance
Yuetian Luo
Rina Foygel Barber
24
0
0
12 Feb 2024
Discovering Causal Relations and Equations from Data
Discovering Causal Relations and Equations from Data
Gustau Camps-Valls
Andreas Gerhardus
Urmi Ninad
Gherardo Varando
Georg Martius
E. Balaguer-Ballester
Ricardo Vinuesa
Emiliano Díaz
L. Zanna
Jakob Runge
PINN
AI4Cl
AI4CE
CML
27
72
0
21 May 2023
Exact Selective Inference with Randomization
Exact Selective Inference with Randomization
Snigdha Panigrahi
Kevin Fry
Jonathan E. Taylor
11
11
0
25 Dec 2022
Conditional Feature Importance for Mixed Data
Conditional Feature Importance for Mixed Data
Kristin Blesch
David S. Watson
Marvin N. Wright
40
7
0
06 Oct 2022
Model-Agnostic Confidence Intervals for Feature Importance: A Fast and
  Powerful Approach Using Minipatch Ensembles
Model-Agnostic Confidence Intervals for Feature Importance: A Fast and Powerful Approach Using Minipatch Ensembles
Luqin Gan
Lili Zheng
Genevera I. Allen
18
6
0
05 Jun 2022
High-dimensional Data Bootstrap
High-dimensional Data Bootstrap
Victor Chernozhukov
Denis Chetverikov
Kengo Kato
Yuta Koike
29
28
0
19 May 2022
Data fission: splitting a single data point
Data fission: splitting a single data point
James Leiner
Boyan Duan
Larry A. Wasserman
Aaditya Ramdas
25
32
0
21 Dec 2021
Test for non-negligible adverse shifts
Test for non-negligible adverse shifts
Vathy M. Kamulete
13
3
0
07 Jul 2021
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
25
16
0
07 Aug 2020
Testing Conditional Independence in Supervised Learning Algorithms
Testing Conditional Independence in Supervised Learning Algorithms
David S. Watson
Marvin N. Wright
CML
18
52
0
28 Jan 2019
Feature Learning and Classification in Neuroimaging: Predicting
  Cognitive Impairment from Magnetic Resonance Imaging
Feature Learning and Classification in Neuroimaging: Predicting Cognitive Impairment from Magnetic Resonance Imaging
Shan Shi
F. Nathoo
11
0
0
17 Jun 2018
Comparison and anti-concentration bounds for maxima of Gaussian random
  vectors
Comparison and anti-concentration bounds for maxima of Gaussian random vectors
Victor Chernozhukov
Denis Chetverikov
Kengo Kato
55
221
0
21 Jan 2013
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