Cover Image

How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ponomareva, Natalia, Xu, Zheng, McMahan, H. Brendan, Kairouz, Peter, Rosenblatt, Lucas, Cohen-Addad, Vincent, Guzmán, Cristóbal, McKenna, Ryan, Andrew, Galen, Bie, Alex, Yu, Da, Kurakin, Alex, Zadimoghaddam, Morteza, Vassilvitskii, Sergei, Terzis, Andreas
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Private prediction for large-scale synthetic text generation
by: Amin, Kareem, et al.
Published: (2024)

JAX-Privacy: A library for differentially private machine learning
by: McKenna, Ryan, et al.
Published: (2026)

Privately Fine-Tuned LLMs Preserve Temporal Dynamics in Tabular Data
by: Rosenblatt, Lucas, et al.
Published: (2026)

It's My Data Too: Private ML for Datasets with Multi-User Training Examples
by: Ganesh, Arun, et al.
Published: (2025)

Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy
by: Koloskova, Anastasia, et al.
Published: (2023)

One-shot Empirical Privacy Estimation for Federated Learning
by: Andrew, Galen, et al.
Published: (2023)

Learning from Synthetic Data: Limitations of ERM
by: Amin, Kareem, et al.
Published: (2026)

Scalable contribution bounding to achieve privacy
by: Cohen-Addad, Vincent, et al.
Published: (2025)

An Inversion Theorem for Buffered Linear Toeplitz (BLT) Matrices and Applications to Streaming Differential Privacy
by: McMahan, H. Brendan, et al.
Published: (2025)

Escaping Collapse: The Strength of Weak Data for Large Language Model Training
by: Amin, Kareem, et al.
Published: (2025)

Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time
by: McMahan, Jeremy
Published: (2024)

Polynomial-Time Approximability of Constrained Reinforcement Learning
by: McMahan, Jeremy
Published: (2025)

Anytime-Constrained Equilibria in Polynomial Time
by: McMahan, Jeremy
Published: (2024)

Scalable Private Partition Selection via Adaptive Weighting
by: Chen, Justin Y., et al.
Published: (2025)

Harnessing large-language models to generate private synthetic text
by: Kurakin, Alexey, et al.
Published: (2023)

Federated Learning in Practice: Reflections and Projections
by: Daly, Katharine, et al.
Published: (2024)

On Design Principles for Private Adaptive Optimizers
by: Ganesh, Arun, et al.
Published: (2025)

Fine-Tuning Large Language Models with User-Level Differential Privacy
by: Charles, Zachary, et al.
Published: (2024)

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?
by: Swanberg, Marika, et al.
Published: (2025)

AI-rithmetic
by: Bie, Alex, et al.
Published: (2026)

Objectively measuring subjectively described traits: geographic variation in body shape and caudal coloration pattern within Vieja melanura (Teleostei: Cichlidae)
by: Caleb D. McMahan
Published: (2017)

A Hassle-free Algorithm for Private Learning in Practice: Don't Use Tree Aggregation, Use BLTs
by: McMahan, H. Brendan, et al.
Published: (2024)

Practical Considerations for Differential Privacy
by: Amin, Kareem, et al.
Published: (2024)

Anytime-Constrained Reinforcement Learning
by: McMahan, Jeremy, et al.
Published: (2023)

Data Poisoning to Fake a Nash Equilibrium in Markov Games
by: Wu, Young, et al.
Published: (2023)

Synthetic Clarification and Correction Dialogues about Data-Centric Tasks -- A Teacher-Student Approach
by: Poelitz, Christian, et al.
Published: (2025)

Hush! Protecting Secrets During Model Training: An Indistinguishability Approach
by: Ganesh, Arun, et al.
Published: (2025)

Scaling up the Banded Matrix Factorization Mechanism for Differentially Private ML
by: McKenna, Ryan
Published: (2024)

Making Sense of Sensemaking: Designing Authentic K-12 STEM Learning Experiences
by: T. J. McKenna
Published: (2025)

Libraries and the Internet. ERIC Digest.
by: McKenna, Mary
Published: (1994)

So Many Students, so Little Time: Practical Student Worker Training in an Academic Library
by: McKenna, Julia
Published: (2020)

HyLife: The Hybrid Library of the Future.
by: McKenna, Brian
Published: (1999)

ANTHROPOLOGY MUST EMBRACE JOURNALISM. PUBLIC PEDAGOGY IS DISCIPLINE'S CHALLENGE
by: Brian McKenna
Published: (2010)

Roping in Uncertainty: Robustness and Regularization in Markov Games
by: McMahan, Jeremy, et al.
Published: (2024)

Synthetic Query Generation for Privacy-Preserving Deep Retrieval Systems using Differentially Private Language Models
by: Carranza, Aldo Gael, et al.
Published: (2023)

DP-λCGD: Efficient Noise Correlation for Differentially Private Model Training
by: Kalinin, Nikita P., et al.
Published: (2026)

Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy
by: Dvijotham, Krishnamurthy, et al.
Published: (2024)

Scaling Laws for Downstream Task Performance of Large Language Models
by: Isik, Berivan, et al.
Published: (2024)

MAPLE: Metadata Augmented Private Language Evolution
by: Chien, Eli, et al.
Published: (2026)

Using Micros to Find Fiction: Issues and Answers.
by: McKenna, Michael C.
Published: (1987)