spliew / shuffgauss
☆10Updated last year
Related projects ⓘ
Alternatives and complementary repositories for shuffgauss
- ☆13Updated last year
- Code repo for the paper "Privacy-aware Compression for Federated Data Analysis".☆16Updated last year
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆31Updated 3 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆30Updated 2 years ago
- Multiple Frequency Estimation Under Local Differential Privacy in Python☆41Updated last year
- ☆23Updated 10 months ago
- ☆22Updated last year
- Python package to create adversarial agents for membership inference attacks againts machine learning models☆47Updated 5 years ago
- Hadamard Response: Communication efficient, sample optimal, linear time locally private learning of distributions☆14Updated 4 years ago
- ☆21Updated 3 years ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆34Updated 3 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆37Updated 2 years ago
- This repo implements several algorithms for learning with differential privacy.☆102Updated last year
- [CVPRW'22] A privacy attack that exploits Adversarial Training models to compromise the privacy of Federated Learning systems.☆12Updated 2 years ago
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆38Updated 5 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆44Updated 6 years ago
- Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.☆52Updated 5 years ago
- ☆16Updated 2 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆129Updated last year
- ☆19Updated last year
- Differentially Private Conditional Generative Adversarial Network☆30Updated 3 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆71Updated 3 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆47Updated 3 years ago
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆100Updated this week
- ☆27Updated last year
- A library for running membership inference attacks against ML models☆139Updated last year
- simple Differential Privacy in PyTorch☆48Updated 4 years ago
- DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.☆25Updated 3 months ago
- ☆45Updated 5 years ago
- Code for Auditing DPSGD☆35Updated 2 years ago