steven7woo / Accuracy-First-Differential-PrivacyLinks
Code for NIPS'2017 paper
☆51Updated 5 years ago
Alternatives and similar repositories for Accuracy-First-Differential-Privacy
Users that are interested in Accuracy-First-Differential-Privacy are comparing it to the libraries listed below
Sorting:
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Updated 4 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Updated 4 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 7 years ago
- This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.☆26Updated 4 years ago
- Differential private machine learning☆195Updated 3 years ago
- Differentially private learning on distributed data (NIPS 2017)☆12Updated 7 years ago
- This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.☆63Updated 6 years ago
- simple Differential Privacy in PyTorch☆48Updated 5 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆49Updated 7 years ago
- ☆44Updated 4 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆33Updated 4 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆275Updated last year
- Hadamard Response: Communication efficient, sample optimal, linear time locally private learning of distributions☆15Updated 5 years ago
- Sample LDP implementation in Python☆129Updated 2 years ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆22Updated 4 years ago
- A library for running membership inference attacks against ML models☆150Updated 2 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆45Updated 3 years ago
- Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.☆76Updated 2 years ago
- Differentially Private Optimization for PyTorch 👁🙅♀️☆189Updated 5 years ago
- Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness (IJCAI'19).☆13Updated 4 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆67Updated 4 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆151Updated 3 years ago
- Source code of paper "Differentially Private Generative Adversarial Network"☆70Updated 6 years ago
- Naive implementation of basic Differential-Privacy framework and algorithms☆48Updated 3 years ago
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆61Updated 5 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆54Updated 6 years ago
- Useful tools for differential privacy☆218Updated 3 years ago
- Simulate a federated setting and run differentially private federated learning.☆381Updated 7 months ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆197Updated 7 years ago