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2006.07749
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Parametric Bootstrap for Differentially Private Confidence Intervals
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
14 June 2020
Cecilia Ferrando
Shufan Wang
Daniel Sheldon
Re-assign community
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Papers citing
"Parametric Bootstrap for Differentially Private Confidence Intervals"
25 / 25 papers shown
Differentially Private E-Values
Daniel Csillag
Diego Mesquita
145
0
0
21 Oct 2025
Differentially Private Linear Regression and Synthetic Data Generation with Statistical Guarantees
Shurong Lin
Aleksandra Slavković
Deekshith Reddy Bhoomireddy
207
1
0
19 Oct 2025
PrivATE: Differentially Private Confidence Intervals for Average Treatment Effects
Maresa Schröder
Justin Hartenstein
Stefan Feuerriegel
470
1
0
27 May 2025
Centering Policy and Practice: Research Gaps around Usable Differential Privacy
Rachel Cummings
Jayshree Sarathy
310
14
0
17 Jun 2024
Statistical Inference for Privatized Data with Unknown Sample Size
Jordan Awan
A. F. Barrientos
Nianqiao P. Ju
345
1
0
10 Jun 2024
Private Regression via Data-Dependent Sufficient Statistic Perturbation
Cecilia Ferrando
Daniel Sheldon
272
4
0
23 May 2024
Bayesian Inference Under Differential Privacy: Prior Selection Considerations with Application to Univariate Gaussian Data and Regression
Zeki Kazan
Jerome P. Reiter
208
1
0
22 May 2024
Uncertainty quantification by block bootstrap for differentially private stochastic gradient descent
Holger Dette
Carina Graw
247
0
0
21 May 2024
Does Differentially Private Synthetic Data Lead to Synthetic Discoveries?
Ileana Montoya Perez
P. Movahedi
Valtteri Nieminen
A. Airola
T. Pahikkala
369
9
0
20 Mar 2024
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation
Gavin Brown
Krishnamurthy Dvijotham
Georgina Evans
Daogao Liu
Adam D. Smith
Abhradeep Thakurta
378
11
0
21 Feb 2024
Resampling methods for private statistical inference
Karan N. Chadha
John C. Duchi
Rohith Kuditipudi
351
3
0
11 Feb 2024
Training Private Models That Know What They Don't Know
Neural Information Processing Systems (NeurIPS), 2023
Stephan Rabanser
Anvith Thudi
Abhradeep Thakurta
Krishnamurthy Dvijotham
Nicolas Papernot
265
10
0
28 May 2023
Simulation-based, Finite-sample Inference for Privatized Data
Journal of the American Statistical Association (JASA), 2023
Jordan Awan
Zhanyu Wang
487
13
0
09 Mar 2023
Differentially Private Distributed Bayesian Linear Regression with MCMC
International Conference on Machine Learning (ICML), 2023
Barics Alparslan
S. Yıldırım
cS. .Ilker Birbil
FedML
293
1
0
31 Jan 2023
Differentially Private Confidence Intervals for Proportions under Stratified Random Sampling
Electronic Journal of Statistics (EJS), 2023
Shurong Lin
Mark Bun
Marco Gaboardi
E. D. Kolaczyk
Adam D. Smith
374
9
0
19 Jan 2023
Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies
Zhanyu Wang
Guang Cheng
Jordan Awan
559
12
0
12 Oct 2022
Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints
Proceedings on Privacy Enhancing Technologies (PoPETs), 2022
Virat Shejwalkar
Arun Ganesh
Rajiv Mathews
Om Thakkar
Abhradeep Thakurta
223
8
0
04 Oct 2022
Privacy Aware Experimentation over Sensitive Groups: A General Chi Square Approach
R. Friedberg
Ryan M. Rogers
290
5
0
17 Aug 2022
Differentially Private Kolmogorov-Smirnov-Type Tests
Electronic Journal of Statistics (EJS), 2022
Jordan Awan
Yue Wang
430
7
0
12 Aug 2022
Hypothesis Testing for Differentially Private Linear Regression
Neural Information Processing Systems (NeurIPS), 2022
Daniel Alabi
Salil P. Vadhan
FedML
205
18
0
29 Jun 2022
Data Augmentation MCMC for Bayesian Inference from Privatized Data
Neural Information Processing Systems (NeurIPS), 2022
Nianqiao P. Ju
Jordan Awan
Ruobin Gong
Vinayak A. Rao
337
27
0
01 Jun 2022
Noise-Aware Statistical Inference with Differentially Private Synthetic Data
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Ossi Raisa
Hibiki Ito
Samuel Kaski
Antti Honkela
SyDa
414
15
0
28 May 2022
Nonparametric extensions of randomized response for private confidence sets
International Conference on Machine Learning (ICML), 2022
Ian Waudby-Smith
Zhiwei Steven Wu
Aaditya Ramdas
351
10
0
17 Feb 2022
Unbiased Statistical Estimation and Valid Confidence Intervals Under Differential Privacy
Christian Covington
Xi He
James Honaker
Gautam Kamath
322
35
0
27 Oct 2021
One Step to Efficient Synthetic Data
Statistica sinica (SS), 2020
Jordan Awan
Zhanrui Cai
543
7
0
03 Jun 2020
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