Private Hypothesis Selection

30 May 2019

Papers citing "Private Hypothesis Selection"

24 / 24 papers shown

Title
Learning with Differentially Private (Sliced) Wasserstein Gradients David Rodríguez-Vítores Clément Lalanne Jean-Michel Loubes FedML 46 0 0 03 Feb 2025
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity A. F. Pour Hassan Ashtiani S. Asoodeh 43 0 0 09 Dec 2023
Instance-Specific Asymmetric Sensitivity in Differential Privacy David Durfee 32 1 0 02 Nov 2023
Private Distribution Learning with Public Data: The View from Sample Compression Shai Ben-David Alex Bie C. Canonne Gautam Kamath Vikrant Singhal 42 11 0 11 Aug 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models Jamil Arbas H. Ashtiani Christopher Liaw 40 23 0 07 Mar 2023
Robustness Implies Privacy in Statistical Estimation Samuel B. Hopkins Gautam Kamath Mahbod Majid Shyam Narayanan 18 50 0 09 Dec 2022
Answering Private Linear Queries Adaptively using the Common Mechanism Yingtai Xiao Guanhong Wang Danfeng Zhang Daniel Kifer 65 7 0 30 Nov 2022
On the Statistical Complexity of Estimation and Testing under Privacy Constraints Clément Lalanne Aurélien Garivier Rémi Gribonval 27 7 0 05 Oct 2022
Private Estimation with Public Data Alex Bie Gautam Kamath Vikrant Singhal 36 28 0 16 Aug 2022
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma Gautam Kamath Argyris Mouzakis Vikrant Singhal FedML 42 26 0 17 May 2022
Private High-Dimensional Hypothesis Testing Shyam Narayanan FedML 40 11 0 03 Mar 2022
Differentially-Private Clustering of Easy Instances E. Cohen Haim Kaplan Yishay Mansour Uri Stemmer Eliad Tsfadia 12 22 0 29 Dec 2021
Private Robust Estimation by Stabilizing Convex Relaxations Pravesh Kothari Pasin Manurangsi A. Velingker 35 46 0 07 Dec 2021
Lower Bounds on the Total Variation Distance Between Mixtures of Two Gaussians Sami Davies A. Mazumdar S. Pal Cyrus Rashtchian 50 11 0 02 Sep 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 28 48 0 24 Jun 2021
On Avoiding the Union Bound When Answering Multiple Differentially Private Queries Badih Ghazi Ravi Kumar Pasin Manurangsi FedML 28 10 0 16 Dec 2020
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 40 41 0 19 Oct 2020
Learning discrete distributions: user vs item-level privacy Yuhan Liu A. Suresh Felix X. Yu Sanjiv Kumar Michael Riley FedML 25 52 0 27 Jul 2020
CoinPress: Practical Private Mean and Covariance Estimation Sourav Biswas Yihe Dong Gautam Kamath Jonathan R. Ullman 39 115 0 11 Jun 2020
Near Instance-Optimality in Differential Privacy Hilal Asi John C. Duchi 26 38 0 16 May 2020
A Primer on Private Statistics Gautam Kamath Jonathan R. Ullman 38 48 0 30 Apr 2020
Differentially Private Assouad, Fano, and Le Cam Jayadev Acharya Ziteng Sun Huanyu Zhang FedML 23 57 0 14 Apr 2020
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 150 420 0 29 Nov 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 72 148 0 01 May 2018