google-research / DP-FTRLLinks
DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.
☆29Updated last month
Alternatives and similar repositories for DP-FTRL
Users that are interested in DP-FTRL are comparing it to the libraries listed below
Sorting:
- Federated Learning Framework Benchmark (UniFed)☆49Updated 2 years ago
- ☆22Updated 2 years ago
- Simplicial-FL to manage client device heterogeneity in Federated Learning☆22Updated last year
- ☆15Updated 2 years ago
- ☆27Updated 2 years ago
- Code repo for the paper "Privacy-aware Compression for Federated Data Analysis".☆19Updated 2 years ago
- A Simulator for Privacy Preserving Federated Learning☆94Updated 4 years ago
- Algorithms for Privacy-Preserving Machine Learning in JAX☆95Updated this week
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆73Updated last year
- DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation☆16Updated 5 years ago
- Federated Learning with Partial Model Personalization☆43Updated 3 years ago
- The code for "Improved Deep Leakage from Gradients" (iDLG).☆152Updated 4 years ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆34Updated 4 years ago
- ☆40Updated last year
- Salvaging Federated Learning by Local Adaptation☆56Updated 11 months ago
- ☆10Updated last year
- Privacy Preserving Vertical Federated Learning☆218Updated 2 years ago
- Privacy attacks on Split Learning☆42Updated 3 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆44Updated 3 years ago
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆123Updated last month
- A codebase that makes differentially private training of transformers easy.☆175Updated 2 years ago
- This repo implements several algorithms for learning with differential privacy.☆108Updated 2 years ago
- ☆80Updated 3 years ago
- A library for running membership inference attacks against ML models☆149Updated 2 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆73Updated 3 years ago
- Official code for "Personalized Federated Learning through Local Memorization" (ICML'22)☆42Updated 2 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆273Updated last year
- Official repo for the paper: Recovering Private Text in Federated Learning of Language Models (in NeurIPS 2022)☆57Updated 2 years ago
- ☆23Updated last year