apple / ml-shuffling-amplificationLinks
☆18Updated 3 years ago
Alternatives and similar repositories for ml-shuffling-amplification
Users that are interested in ml-shuffling-amplification are comparing it to the libraries listed below
Sorting:
- Analytic calibration for differential privacy with Gaussian perturbations☆48Updated 6 years ago
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆73Updated last year
- ☆38Updated 3 years ago
- Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.☆75Updated last year
- autodp: A flexible and easy-to-use package for differential privacy☆274Updated last year
- Multiple Frequency Estimation Under Local Differential Privacy in Python☆49Updated 2 years ago
- Unified, Simplified, Tight and Fast Privacy Amplification in the Shuffle Model of Differential Privacy☆11Updated 10 months ago
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆59Updated 5 years ago
- Sample LDP implementation in Python☆129Updated 2 years ago
- Differential private machine learning☆195Updated 3 years ago
- An implementation of "Data Synthesis via Differentially Private Markov Random Fields"☆13Updated last year
- A library providing general-purpose tools for estimating discrete distributions from noisy observations of their marginals.☆105Updated last week
- ☆43Updated 4 years ago
- A SMPC companion library for Syft☆104Updated 2 months ago
- list of differential-privacy related resources☆314Updated 7 months ago
- The core library of differential privacy algorithms powering the OpenDP Project.☆379Updated this week
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆127Updated 3 weeks ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆22Updated 4 years ago
- This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.☆63Updated 6 years ago
- Implementations of differentially private release mechanisms for graph statistics☆24Updated 3 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- Code for computing tight guarantees for differential privacy☆23Updated 2 years ago
- The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy☆531Updated 11 months ago
- Hadamard Response: Communication efficient, sample optimal, linear time locally private learning of distributions☆14Updated 4 years ago
- A secure aggregation system for private federated learning☆41Updated last year
- Privacy Preserving Vertical Federated Learning☆218Updated 2 years ago
- Locally Private Graph Neural Networks (ACM CCS 2021)☆49Updated 2 months ago
- Secure Aggregation for FL☆35Updated last year
- Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness (IJCAI'19).☆13Updated 4 years ago
- A large labelled image dataset for benchmarking in federated learning☆100Updated last year