Private Distribution Learning with Public Data: The View from Sample
Compression

Private Distribution Learning with Public Data: The View from Sample Compression

11 August 2023

Vikrant Singhal

Papers citing "Private Distribution Learning with Public Data: The View from Sample Compression"

16 / 16 papers shown

Title
Optimal Differentially Private Sampling of Unbounded Gaussians Valentio Iverson Gautam Kamath Argyris Mouzakis 34 0 0 03 Mar 2025
Differentially Private Prototypes for Imbalanced Transfer Learning Dariush Wahdany Matthew Jagielski Adam Dziedzic Franziska Boenisch 72 0 0 17 Feb 2025
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses Mathieu Bazinet Valentina Zantedeschi Pascal Germain MLT AI4CE 16 2 0 26 Sep 2024
Credit Attribution and Stable Compression Roi Livni Shay Moran Kobbi Nissim Chirag Pabbaraju 25 0 0 22 Jun 2024
Public-data Assisted Private Stochastic Optimization: Power and Limitations Enayat Ullah Michael Menart Raef Bassily Cristóbal Guzmán Raman Arora 30 1 0 06 Mar 2024
Oracle-Efficient Differentially Private Learning with Public Data Adam Block Mark Bun Rathin Desai Abhishek Shetty Steven Wu FedML 11 2 0 13 Feb 2024
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity A. F. Pour Hassan Ashtiani S. Asoodeh 18 0 0 09 Dec 2023
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples Mohammad Afzali H. Ashtiani Christopher Liaw 17 5 0 07 Sep 2023
Differentially Private Domain Adaptation with Theoretical Guarantees Raef Bassily Corinna Cortes Anqi Mao M. Mohri 12 0 0 15 Jun 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models Jamil Arbas H. Ashtiani Christopher Liaw 24 22 0 07 Mar 2023
A Private and Computationally-Efficient Estimator for Unbounded Gaussians Gautam Kamath Argyris Mouzakis Vikrant Singhal Thomas Steinke Jonathan R. Ullman 45 38 0 08 Nov 2021
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 344 0 13 Oct 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning Da Yu Huishuai Zhang Wei Chen Tie-Yan Liu FedML SILM 91 110 0 25 Feb 2021
Leveraging Public Data for Practical Private Query Release Terrance Liu G. Vietri Thomas Steinke Jonathan R. Ullman Zhiwei Steven Wu 142 58 0 17 Feb 2021
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 30 40 0 19 Oct 2020
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 52 146 0 01 May 2018