Privately Learning High-Dimensional Distributions

1 May 2018

Papers citing "Privately Learning High-Dimensional Distributions"

40 / 40 papers shown

Title
Learning with Differentially Private (Sliced) Wasserstein Gradients Clément Lalanne Jean-Michel Loubes David Rodríguez-Vítores FedML 46 0 0 03 Feb 2025
Private Means and the Curious Incident of the Free Lunch Jack Fitzsimons James Honaker Michael Shoemate Vikrant Singhal 46 2 0 19 Aug 2024
On Differentially Private U Statistics Kamalika Chaudhuri Po-Ling Loh Shourya Pandey Purnamrita Sarkar FedML 64 0 0 06 Jul 2024
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity A. F. Pour Hassan Ashtiani S. Asoodeh 41 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
Mean Estimation Under Heterogeneous Privacy: Some Privacy Can Be Free Syomantak Chaudhuri T. Courtade 30 4 0 27 Apr 2023
Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning T. Tony Cai Yichen Wang Linjun Zhang 46 16 0 13 Mar 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models Jamil Arbas H. Ashtiani Christopher Liaw 40 23 0 07 Mar 2023
Information Theoretic Lower Bounds for Information Theoretic Upper Bounds Roi Livni 13 14 0 09 Feb 2023
On Private and Robust Bandits Yulian Wu Xingyu Zhou Youming Tao Di Wang 24 5 0 06 Feb 2023
A Fast Algorithm for Adaptive Private Mean Estimation John C. Duchi Saminul Haque Rohith Kuditipudi FedML 27 15 0 17 Jan 2023
DP-SIPS: A simpler, more scalable mechanism for differentially private partition selection Marika Swanberg Damien Desfontaines Samuel Haney 36 6 0 05 Jan 2023
Robustness Implies Privacy in Statistical Estimation Samuel B. Hopkins Gautam Kamath Mahbod Majid Shyam Narayanan 18 50 0 09 Dec 2022
Private Estimation with Public Data Alex Bie Gautam Kamath Vikrant Singhal 36 28 0 16 Aug 2022
Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions Omri Ben-Eliezer Dan Mikulincer Ilias Zadik FedML 58 7 0 15 Aug 2022
Measuring Forgetting of Memorized Training Examples Matthew Jagielski Om Thakkar Florian Tramèr Daphne Ippolito Katherine Lee ... Eric Wallace Shuang Song Abhradeep Thakurta Nicolas Papernot Chiyuan Zhang TDI 66 102 0 30 Jun 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 37 11 0 03 Mar 2022
Differentially Private Regression with Unbounded Covariates Jason Milionis Alkis Kalavasis Dimitris Fotakis Stratis Ioannidis 23 10 0 19 Feb 2022
Provably Private Distributed Averaging Consensus: An Information-Theoretic Approach Mohammad Fereydounian Aryan Mokhtari Ramtin Pedarsani Hamed Hassani FedML 27 2 0 18 Feb 2022
Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms Alireza Fallah A. Makhdoumi Azarakhsh Malekian Asuman Ozdaglar FedML 30 29 0 10 Jan 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
Differential Privacy Over Riemannian Manifolds M. Reimherr Karthik Bharath Carlos Soto 32 17 0 03 Nov 2021
Tight and Robust Private Mean Estimation with Few Users Cheng-Han Chiang Vahab Mirrokni Hung-yi Lee FedML 31 28 0 22 Oct 2021
FriendlyCore: Practical Differentially Private Aggregation Eliad Tsfadia E. Cohen Haim Kaplan Yishay Mansour Uri Stemmer 20 33 0 19 Oct 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
Optimal Private Median Estimation under Minimal Distributional Assumptions Christos Tzamos Emmanouil-Vasileios Vlatakis-Gkaragkounis Ilias Zadik 27 21 0 12 Nov 2020
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds T. Tony Cai Yichen Wang Linjun Zhang FedML 43 20 0 08 Nov 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
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
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation Mark Bun Thomas Steinke 47 74 0 06 Jun 2019
Private Identity Testing for High-Dimensional Distributions C. Canonne Gautam Kamath Audra McMillan Jonathan R. Ullman Lydia Zakynthinou 37 36 0 28 May 2019
Locally Private Gaussian Estimation Matthew Joseph Janardhan Kulkarni Jieming Mao Zhiwei Steven Wu FedML 37 38 0 20 Nov 2018
Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing Marco Gaboardi H. Lim Ryan M. Rogers Salil P. Vadhan 45 138 0 07 Feb 2016